From 63d22063743b6716a440bf0c5f92336f7d132a98 Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Mon, 15 Apr 2024 22:05:07 +0000 Subject: [PATCH] build based on 04b9210 --- previews/PR284/.documenter-siteinfo.json | 2 +- previews/PR284/api/index.html | 80 +++++++++---------- previews/PR284/assets/examples/1-seq.html | 6 +- previews/PR284/assets/examples/1-signal.html | 6 +- previews/PR284/assets/examples/1-signal2.html | 6 +- .../PR284/assets/examples/2-phantom1.html | 6 +- .../PR284/assets/examples/2-phantom2.html | 6 +- previews/PR284/assets/examples/2-recon.html | 6 +- previews/PR284/assets/examples/2-seq.html | 6 +- previews/PR284/assets/examples/2-signal.html | 6 +- previews/PR284/assets/examples/3-phantom.html | 6 +- previews/PR284/assets/examples/3-profile.html | 6 +- previews/PR284/assets/examples/3-recon1.html | 6 +- previews/PR284/assets/examples/3-recon2.html | 6 +- previews/PR284/assets/examples/3-recon3.html | 6 +- previews/PR284/assets/examples/3-seq.html | 6 +- previews/PR284/assets/examples/3-signal.html | 6 +- previews/PR284/assets/examples/42-seq.html | 6 +- .../PR284/assets/examples/4a-profile.html | 6 +- .../PR284/assets/examples/4b-profile.html | 6 +- .../PR284/create-your-own-phantom/index.html | 2 +- .../PR284/create-your-own-sequence/index.html | 2 +- .../educational-1d-simulation/index.html | 2 +- previews/PR284/events/index.html | 2 +- .../generated/examples/01-FID/index.html | 2 +- .../02-SmallTipApproximation/index.html | 2 +- .../examples/03-ChemicalShiftEPI/index.html | 2 +- .../examples/04-3DSliceSelective/index.html | 2 +- previews/PR284/getting-started/index.html | 2 +- previews/PR284/index.html | 2 +- previews/PR284/mri-theory-informal/index.html | 2 +- previews/PR284/mri-theory/index.html | 2 +- previews/PR284/notebooks/index.html | 2 +- .../PR284/programming-workflow/index.html | 2 +- previews/PR284/sequence/index.html | 2 +- previews/PR284/ui-details/index.html | 2 +- previews/PR284/ways-of-using-koma/index.html | 2 +- 37 files changed, 112 insertions(+), 112 deletions(-) diff --git a/previews/PR284/.documenter-siteinfo.json b/previews/PR284/.documenter-siteinfo.json index 4c654ad6a..24e77a1e6 100644 --- a/previews/PR284/.documenter-siteinfo.json +++ b/previews/PR284/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-04-15T21:55:08","documenter_version":"1.4.0"}} \ No newline at end of file +{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-04-15T22:04:55","documenter_version":"1.4.0"}} \ No newline at end of file diff --git a/previews/PR284/api/index.html b/previews/PR284/api/index.html index e5596d57a..81d8f9d1b 100644 --- a/previews/PR284/api/index.html +++ b/previews/PR284/api/index.html @@ -4,103 +4,103 @@ julia> out1, out2 = component_name(arg1, arg2; kw1=valkw1, kw2=valkw2)

The preceding docstring block will always start with the way the component is called (outputs = component_name(inputs), followed by a brief description of what the component does. If necessary, a note block will be displayed. In general, the following subsections are optional: Arguments, Keywords, Returns, References, and Examples, but they will be provided as needed. These subsections are self-explanatory, making it intuitive to understand their purpose.

Please note that every subitem in the sections Arguments, Keywords, and Returns represents variables. They include practical information along with a description. The information enclosed in parentheses is optional but highly useful when provided.

Structs

Scanner

KomaMRIBase.Scanner — Type
sys = Scanner(B0, B1, Gmax, Smax, ADC_Δt, seq_Δt, GR_Δt, RF_Δt,
     RF_ring_down_T, RF_dead_time_T, ADC_dead_time_T)

The Scanner struct. It contains hardware limitations of the MRI resonator. It is an input for the simulation.

Arguments

  • B0: (::Real, =1.5, [T]) main magnetic field strength
  • B1: (::Real, =10e-6, [T]) maximum RF amplitude
  • Gmax: (::Real, =60e-3, [T/m]) maximum gradient amplitude
  • Smax: (::Real, =500, [mT/m/ms]) gradient's maximum slew-rate
  • ADC_Δt: (::Real, =2e-6, [s]) ADC raster time
  • seq_Δt: (::Real, =1e-5, [s]) sequence-block raster time
  • GR_Δt: (::Real, =1e-5, [s]) gradient raster time
  • RF_Δt: (::Real, =1e-6, [s]) RF raster time
  • RF_ring_down_T: (::Real, =20e-6, [s]) RF ring down time
  • RF_dead_time_T: (::Real, =100e-6, [s]) RF dead time
  • ADC_dead_time_T: (::Real, =10e-6, [s]) ADC dead time

Returns

  • sys: (::Scanner) Scanner struct

Examples

julia> sys = Scanner()
 
-julia> sys.B0
source

Phantom

KomaMRIBase.Phantom — Type
obj = Phantom(name, x, y, z, ρ, T1, T2, T2s, Δw, Dλ1, Dλ2, Dθ, ux, uy, uz)

The Phantom struct. Most of its field names are vectors, with each element associated with a property value representing a spin. This struct serves as an input for the simulation.

Arguments

  • name: (::String) phantom name
  • x: (::AbstractVector{T<:Real}, [m]) spin x-position vector
  • y: (::AbstractVector{T<:Real}, [m]) spin y-position vector
  • z: (::AbstractVector{T<:Real}, [m]) spin z-position vector
  • ρ: (::AbstractVector{T<:Real}) spin proton density vector
  • T1: (::AbstractVector{T<:Real}, [s]) spin T1 parameter vector
  • T2: (::AbstractVector{T<:Real}, [s]) spin T2 parameter vector
  • T2s: (::AbstractVector{T<:Real}, [s]) spin T2s parameter vector
  • Δw: (::AbstractVector{T<:Real}, [rad/s]) spin off-resonance parameter vector
  • Dλ1: (::AbstractVector{T<:Real}) spin Dλ1 (diffusion) parameter vector
  • Dλ2: (::AbstractVector{T<:Real}) spin Dλ2 (diffusion) parameter vector
  • Dθ: (::AbstractVector{T<:Real}) spin Dθ (diffusion) parameter vector
  • ux: (::Function) displacement field in the x-axis
  • uy: (::Function) displacement field in the y-axis
  • uz: (::Function) displacement field in the z-axis

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj = Phantom(x=[0.0])
+julia> sys.B0
source

Phantom

KomaMRIBase.Phantom — Type
obj = Phantom(name, x, y, z, ρ, T1, T2, T2s, Δw, Dλ1, Dλ2, Dθ, ux, uy, uz)

The Phantom struct. Most of its field names are vectors, with each element associated with a property value representing a spin. This struct serves as an input for the simulation.

Arguments

  • name: (::String) phantom name
  • x: (::AbstractVector{T<:Real}, [m]) spin x-position vector
  • y: (::AbstractVector{T<:Real}, [m]) spin y-position vector
  • z: (::AbstractVector{T<:Real}, [m]) spin z-position vector
  • ρ: (::AbstractVector{T<:Real}) spin proton density vector
  • T1: (::AbstractVector{T<:Real}, [s]) spin T1 parameter vector
  • T2: (::AbstractVector{T<:Real}, [s]) spin T2 parameter vector
  • T2s: (::AbstractVector{T<:Real}, [s]) spin T2s parameter vector
  • Δw: (::AbstractVector{T<:Real}, [rad/s]) spin off-resonance parameter vector
  • Dλ1: (::AbstractVector{T<:Real}) spin Dλ1 (diffusion) parameter vector
  • Dλ2: (::AbstractVector{T<:Real}) spin Dλ2 (diffusion) parameter vector
  • Dθ: (::AbstractVector{T<:Real}) spin Dθ (diffusion) parameter vector
  • ux: (::Function) displacement field in the x-axis
  • uy: (::Function) displacement field in the y-axis
  • uz: (::Function) displacement field in the z-axis

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj = Phantom(x=[0.0])
 
-julia> obj.ρ
source
KomaMRIBase.brain_phantom2D — Function
obj = brain_phantom2D(; axis="axial", ss=4, us=1)

Creates a two-dimensional brain Phantom struct. Default ss=4 sample spacing is 2 mm. Original file (ss=1) sample spacing is .5 mm.

References

  • B. Aubert-Broche, D.L. Collins, A.C. Evans: "A new improved version of the realistic digital brain phantom" NeuroImage, in review - 2006
  • B. Aubert-Broche, M. Griffin, G.B. Pike, A.C. Evans and D.L. Collins: "20 new digital brain phantoms for creation of validation image data bases" IEEE TMI, in review - 2006
  • https://brainweb.bic.mni.mcgill.ca/brainweb

Keywords

  • axis: (::String, ="axial", opts=["axial", "coronal", "sagittal"]) orientation of the phantom
  • ss: (::Integer or ::Vector{Integer}, =4) subsampling parameter for all axes if scaler, per axis if 2 element vector [ssx, ssy]
  • us: (::Integer or ::Vector{Integer}, =1) upsampling parameter for all axes if scaler, per axis if 2 element vector [usx, usy], if used ss is set to ss=1

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj = brain_phantom2D(; axis="sagittal", ss=1)
+julia> obj.ρ
source
KomaMRIBase.brain_phantom2D — Function
obj = brain_phantom2D(; axis="axial", ss=4, us=1)

Creates a two-dimensional brain Phantom struct. Default ss=4 sample spacing is 2 mm. Original file (ss=1) sample spacing is .5 mm.

References

  • B. Aubert-Broche, D.L. Collins, A.C. Evans: "A new improved version of the realistic digital brain phantom" NeuroImage, in review - 2006
  • B. Aubert-Broche, M. Griffin, G.B. Pike, A.C. Evans and D.L. Collins: "20 new digital brain phantoms for creation of validation image data bases" IEEE TMI, in review - 2006
  • https://brainweb.bic.mni.mcgill.ca/brainweb

Keywords

  • axis: (::String, ="axial", opts=["axial", "coronal", "sagittal"]) orientation of the phantom
  • ss: (::Integer or ::Vector{Integer}, =4) subsampling parameter for all axes if scaler, per axis if 2 element vector [ssx, ssy]
  • us: (::Integer or ::Vector{Integer}, =1) upsampling parameter for all axes if scaler, per axis if 2 element vector [usx, usy], if used ss is set to ss=1

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj = brain_phantom2D(; axis="sagittal", ss=1)
 
 julia> obj = brain_phantom2D(; axis="axial", us=[1, 2])
 
-julia> plot_phantom_map(obj, :ρ)
source
KomaMRIBase.brain_phantom3D — Function
obj = brain_phantom3D(; ss=4, us=1)

Creates a three-dimentional brain Phantom struct. Default ss=4 sample spacing is 2 mm. Original file (ss=1) sample spacing is .5 mm.

References

  • B. Aubert-Broche, D.L. Collins, A.C. Evans: "A new improved version of the realistic digital brain phantom" NeuroImage, in review - 2006
  • B. Aubert-Broche, M. Griffin, G.B. Pike, A.C. Evans and D.L. Collins: "20 new digital brain phantoms for creation of validation image data bases" IEEE TMI, in review - 2006
  • https://brainweb.bic.mni.mcgill.ca/brainweb

Keywords

  • ss: (::Integer or ::Vector{Integer}, =4) subsampling parameter for all axes if scaler, per axis if 3 element vector [ssx, ssy, ssz]
  • us: (::Integer or ::Vector{Integer}, =1) upsampling parameter for all axes if scaler, per axis if 3 element vector [usx, usy, usz]
  • start_end: (::Vector{Integer}, =[160,200]) z index range of presampled phantom, 180 is center

Returns

  • obj: (::Phantom) 3D Phantom struct

Examples

julia> obj = brain_phantom3D(; ss=5)
+julia> plot_phantom_map(obj, :ρ)
source
KomaMRIBase.brain_phantom3D — Function
obj = brain_phantom3D(; ss=4, us=1)

Creates a three-dimentional brain Phantom struct. Default ss=4 sample spacing is 2 mm. Original file (ss=1) sample spacing is .5 mm.

References

  • B. Aubert-Broche, D.L. Collins, A.C. Evans: "A new improved version of the realistic digital brain phantom" NeuroImage, in review - 2006
  • B. Aubert-Broche, M. Griffin, G.B. Pike, A.C. Evans and D.L. Collins: "20 new digital brain phantoms for creation of validation image data bases" IEEE TMI, in review - 2006
  • https://brainweb.bic.mni.mcgill.ca/brainweb

Keywords

  • ss: (::Integer or ::Vector{Integer}, =4) subsampling parameter for all axes if scaler, per axis if 3 element vector [ssx, ssy, ssz]
  • us: (::Integer or ::Vector{Integer}, =1) upsampling parameter for all axes if scaler, per axis if 3 element vector [usx, usy, usz]
  • start_end: (::Vector{Integer}, =[160,200]) z index range of presampled phantom, 180 is center

Returns

  • obj: (::Phantom) 3D Phantom struct

Examples

julia> obj = brain_phantom3D(; ss=5)
 
 julia> obj = brain_phantom3D(; us=[2, 2, 1])
 
-julia> plot_phantom_map(obj, :ρ)
source
KomaMRIBase.pelvis_phantom2D — Function
obj = pelvis_phantom2D(; ss=4, us=1)

Creates a two-dimensional pelvis Phantom struct. Default ss=4 sample spacing is 2 mm. Original file (ss=1) sample spacing is .5 mm.

Keywords

  • ss: (::Integer or ::Vector{Integer}, =4) subsampling parameter for all axes if scaler, per axis if 2 element vector [ssx, ssy]
  • us: (::Integer or ::Vector{Integer}, =1) upsampling parameter for all axes if scaler, per axis if 2 element vector [usx, usy]

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj = pelvis_phantom2D(; ss=2])
+julia> plot_phantom_map(obj, :ρ)
source
KomaMRIBase.pelvis_phantom2D — Function
obj = pelvis_phantom2D(; ss=4, us=1)

Creates a two-dimensional pelvis Phantom struct. Default ss=4 sample spacing is 2 mm. Original file (ss=1) sample spacing is .5 mm.

Keywords

  • ss: (::Integer or ::Vector{Integer}, =4) subsampling parameter for all axes if scaler, per axis if 2 element vector [ssx, ssy]
  • us: (::Integer or ::Vector{Integer}, =1) upsampling parameter for all axes if scaler, per axis if 2 element vector [usx, usy]

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj = pelvis_phantom2D(; ss=2])
 
 julia> obj = pelvis_phantom2D(; us=[1, 2])
 
-julia> pelvis_phantom2D(obj, :ρ)
source

Sequence

KomaMRIBase.Sequence — Type
seq = Sequence()
+julia> pelvis_phantom2D(obj, :ρ)
source

Sequence

KomaMRIBase.Sequence — Type
seq = Sequence()
 seq = Sequence(GR)
 seq = Sequence(GR, RF)
 seq = Sequence(GR, RF, ADC)
 seq = Sequence(GR, RF, ADC, DUR)
 seq = Sequence(GR::Array{Grad,1})
 seq = Sequence(GR::Array{Grad,1}, RF::Array{RF,1})
-seq = Sequence(GR::Array{Grad,1}, RF::Array{RF,1}, A::ADC, DUR, DEF)

The Sequence struct. It contains events of an MRI sequence. Most field names (except for the DEF field) consist of matrices or vectors, where each column index represents a sequence block. This struct serves as an input for the simulation.

Arguments

  • GR: (::Matrix{Grad}) gradient matrix. Rows for x-y-z amplitudes and columns are for blocks
  • RF: (::Matrix{RF}) RF matrix. The 1 row is for the coil and columns are for blocks
  • ADC: (::Array{ADC,1}) ADC block vector
  • DUR: (::Vector, [s]) duration block vector
  • DEF: (::Dict{String, Any}) dictionary with relevant information of the sequence. Possible keys could be ["AdcRasterTime", "GradientRasterTime", "Name", "Nz", "Num_Blocks", "Nx", "Ny", "PulseqVersion", "BlockDurationRaster", "FileName", "RadiofrequencyRasterTime"]

Returns

  • seq: (::Sequence) Sequence struct
source

Grad

KomaMRIBase.Grad — Type
gr = Grad(A, T)
+seq = Sequence(GR::Array{Grad,1}, RF::Array{RF,1}, A::ADC, DUR, DEF)

The Sequence struct. It contains events of an MRI sequence. Most field names (except for the DEF field) consist of matrices or vectors, where each column index represents a sequence block. This struct serves as an input for the simulation.

Arguments

  • GR: (::Matrix{Grad}) gradient matrix. Rows for x-y-z amplitudes and columns are for blocks
  • RF: (::Matrix{RF}) RF matrix. The 1 row is for the coil and columns are for blocks
  • ADC: (::Array{ADC,1}) ADC block vector
  • DUR: (::Vector, [s]) duration block vector
  • DEF: (::Dict{String, Any}) dictionary with relevant information of the sequence. Possible keys could be ["AdcRasterTime", "GradientRasterTime", "Name", "Nz", "Num_Blocks", "Nx", "Ny", "PulseqVersion", "BlockDurationRaster", "FileName", "RadiofrequencyRasterTime"]

Returns

  • seq: (::Sequence) Sequence struct
source

Grad

KomaMRIBase.Grad — Type
gr = Grad(A, T)
 gr = Grad(A, T, rise)
 gr = Grad(A, T, rise, delay)
 gr = Grad(A, T, rise, fall, delay)
 gr = Grad(A, T, rise, fall, delay, first, last)

The Grad struct represents a gradient of a sequence event.

Arguments

  • A: (::Real or ::Vector, [T/m]) amplitude of the gradient
  • T: (::Real or ::Vector, [s]) duration of the flat-top
  • rise: (::Real, [s]) duration of the rise
  • fall: (::Real, [s]) duration of the fall
  • delay: (::Real, [s]) duration of the delay

Returns

  • gr: (::Grad) gradient struct

Examples

julia> gr = Grad(1, 1, 0.1, 0.1, 0.2)
 
-julia> seq = Sequence([gr]); plot_seq(seq)
source
KomaMRIBase.Grad — Method
gr = Grad(f::Function, T::Real, N::Integer; delay::Real)

Generates an arbitrary gradient waveform defined by the function f in the interval t ∈ [0,T]. The time separation between two consecutive samples is given by T/(N-1).

Arguments

  • f: (::Function) function that describes the gradient waveform
  • T: (::Real, [s]) duration of the gradient waveform
  • N: (::Integer, =300) number of samples of the gradient waveform

Keywords

  • delay: (::Real, =0, [s]) delay time of the waveform

Returns

  • gr: (::Grad) gradient struct

Examples

julia> gx = Grad(t -> sin(π*t / 0.8), 0.8)
+julia> seq = Sequence([gr]); plot_seq(seq)
source
KomaMRIBase.Grad — Method
gr = Grad(f::Function, T::Real, N::Integer; delay::Real)

Generates an arbitrary gradient waveform defined by the function f in the interval t ∈ [0,T]. The time separation between two consecutive samples is given by T/(N-1).

Arguments

  • f: (::Function) function that describes the gradient waveform
  • T: (::Real, [s]) duration of the gradient waveform
  • N: (::Integer, =300) number of samples of the gradient waveform

Keywords

  • delay: (::Real, =0, [s]) delay time of the waveform

Returns

  • gr: (::Grad) gradient struct

Examples

julia> gx = Grad(t -> sin(π*t / 0.8), 0.8)
 
-julia> seq = Sequence([gx]); plot_seq(seq)
source

RF

KomaMRIBase.RF — Type
rf = RF(A, T)
+julia> seq = Sequence([gx]); plot_seq(seq)
source

RF

KomaMRIBase.RF — Type
rf = RF(A, T)
 rf = RF(A, T, Δf)
 rf = RF(A, T, Δf, delay)

The RF struct represents a Radio Frequency excitation of a sequence event.

Arguments

  • A: (::Complex, [T]) RF complex amplitud modulation (AM), $B_1(t) = |B_1(t)| e^{i\phi(t)} = B_{1}(t) + iB_{1,y}(t)$
  • T: (::Real, [s]) RF duration
  • Δf: (::Real or ::Vector, [Hz]) RF frequency difference with respect to the Larmor frequency. This can be a number but also a vector to represent frequency modulated signals (FM).
  • delay: (::Real, [s]) RF delay time

Returns

  • rf: (::RF) the RF struct

Examples

julia> rf = RF(1, 1, 0, 0.2)
 
-julia> seq = Sequence(); seq += rf; plot_seq(seq)
source

ADC

KomaMRIBase.ADC — Type
adc = ADC(N, T)
+julia> seq = Sequence(); seq += rf; plot_seq(seq)
source

ADC

KomaMRIBase.ADC — Type
adc = ADC(N, T)
 adc = ADC(N, T, delay)
 adc = ADC(N, T, delay, Δf, ϕ)

The ADC struct represents the Analog to Digital Converter (ADC) of a sequence event.

Arguments

  • N: (::Int64) number of acquired samples
  • T: (::Float64, [s]) duration to acquire the samples
  • delay: (::Float64, [s]) delay time to start the acquisition
  • Δf: (::Float64, [Hz]) delta frequency. It is meant to compensate RF pulse phases
  • ϕ: (::Float64, [rad]) phase. It is meant to compensate RF pulse phases

Returns

  • adc: (::ADC) ADC struct

Examples

julia> adc = ADC(16, 1, 0.1)
 
-julia> seq = Sequence(); seq += adc; plot_seq(seq)
source

Delay

KomaMRIBase.Delay — Type
delay = Delay(T)

The Delay struct is meant to add a delay to a sequence by using a sum operator.

Arguments

  • T: (::Real, [s]) time delay value

Returns

  • delay: (::Delay) delay struct

Examples

julia> delay = Delay(0.5)
+julia> seq = Sequence(); seq += adc; plot_seq(seq)
source

Delay

KomaMRIBase.Delay — Type
delay = Delay(T)

The Delay struct is meant to add a delay to a sequence by using a sum operator.

Arguments

  • T: (::Real, [s]) time delay value

Returns

  • delay: (::Delay) delay struct

Examples

julia> delay = Delay(0.5)
 
 julia> s = Sequence([Grad(1, 1, 0.1)])
 
-julia> seq = delay + s; plot_seq(seq)
source

dur

KomaMRIBase.dur — Function
y = dur(x::Grad)
-y = dur(x::Vector{Grad})

Duration time in [s] of Grad struct or Grad array. When the input is a gradient vector, then the duration is the maximum duration of all the elements of the gradient vector.

Arguments

  • x: (::Grad or ::Vector{Grad}) RF struct or RF array

Returns

  • y: (::Float64, [s]) duration of the RF struct or RF array
source
y = dur(x::RF)
+julia> seq = delay + s; plot_seq(seq)
source

dur

KomaMRIBase.dur — Function
y = dur(x::Grad)
+y = dur(x::Vector{Grad})

Duration time in [s] of Grad struct or Grad array. When the input is a gradient vector, then the duration is the maximum duration of all the elements of the gradient vector.

Arguments

  • x: (::Grad or ::Vector{Grad}) RF struct or RF array

Returns

  • y: (::Float64, [s]) duration of the RF struct or RF array
source
y = dur(x::RF)
 y = dur(x::Array{RF,1})
-y = dur(x::Array{RF,2})

Duration time in [s] of RF struct or RF array.

Arguments

  • x: (::RF or ::Array{RF,1} or ::Array{RF,2}) RF struct or RF array

Returns

  • y: (::Float64, [s]) duration of the RF struct or RF array
source
T = dur(x::Sequence)

The total duration of the sequence in [s].

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • T: (::Real, [s]) total duration of the sequence
source

rotx

KomaMRIBase.rotx — Function
Rx = rotx(θ::Real)

Rotates vector counter-clockwise with respect to the x-axis.

Arguments

  • θ: (::Real, [rad]) rotation angle

Returns

  • Rx: (::Matrix{Int64}) rotation matrix
source

roty

KomaMRIBase.roty — Function
Ry = roty(θ::Real)

Rotates vector counter-clockwise with respect to the y-axis.

Arguments

  • θ: (::Real, [rad]) rotation angle

Returns

  • Ry: (::Matrix{Int64}) rotation matrix
source

rotz

KomaMRIBase.rotz — Function
Rz = rotz(θ::Real)

Rotates vector counter-clockwise with respect to the z-axis.

Arguments

  • θ: (::Real, [rad]) rotation angle

Returns

  • Rz: (::Matrix{Int64}) rotation matrix
source

get_Mk

KomaMRIBase.get_Mk — Function
Mk, Mk_adc = get_Mk(seq::Sequence, k; Δt=1, skip_rf=zeros(Bool, sum(is_RF_on.(seq))))

Computes the $k$th-order moment of the Sequence seq given by the formula $\int_0^T t^k G(t) dt$.

Arguments

  • seq: (::Sequence) Sequence struct
  • k: (::Integer) order of the moment to be computed
  • Δt: (::Real, =1, [s]) nominal delta time separation between two time samples for ADC acquisition and Gradients
  • skip_rf: (::Vector{Bool}, =zeros(Bool, sum(is_RF_on.(seq)))) boolean vector which indicates whether to skip the computation for resetting the integral for excitation or refocusing RF type

Returns

  • Mk: (3-column ::Matrix{Real}) $k$th-order moment
  • Mk_adc: (3-column ::Matrix{Real}) $k$th-order moment sampled at ADC times
source

get_kspace

KomaMRIBase.get_kspace — Function

Computes the k-space trajectory of the Sequence seq. Refer to get_Mk and get_M0

source

get_M0

KomaMRIBase.get_M0 — Function

Computes the zero-order moment of the Sequence seq. Refer to get_Mk and get_kspace

source

get_M1

KomaMRIBase.get_M1 — Function

Computes the 1st-order moment of the Sequence seq. Refer to get_Mk

source

get_M2

KomaMRIBase.get_M2 — Function

Computes the 2nd-order moment of the Sequence seq. Refer to get_Mk

source

get_flip_angles

KomaMRIBase.get_flip_angles — Function
y = get_flip_angles(x::Sequence)

Returns all the flip angles of the RF pulses in the sequence x.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Vector{Float64}, [deg]) flip angles
source

is_RF_on

KomaMRIBase.is_RF_on — Function
y = is_RF_on(x::Sequence)
-y = is_RF_on(x::Sequence, t::Vector{Float64})

Tells if the sequence seq has elements with RF active, or active during time t.

Arguments

  • x: (::Sequence) Sequence struct
  • t: (::Vector{Float64}, [s]) time to check

Returns

  • y: (::Bool) boolean that tells whether or not the RF in the sequence is active
source

is_GR_on

KomaMRIBase.is_GR_on — Function
y = is_GR_on(x::Sequence)

Tells if the sequence seq has elements with GR active.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GR in the sequence is active
source

is_Gx_on

KomaMRIBase.is_Gx_on — Function
y = is_Gx_on(x::Sequence)

Tells if the sequence seq has elements with GR active in x direction.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GRx in the sequence is active
source

is_Gy_on

KomaMRIBase.is_Gy_on — Function
y = is_Gy_on(x::Sequence)

Tells if the sequence seq has elements with GR active in y direction.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GRy in the sequence is active
source

is_Gz_on

KomaMRIBase.is_Gz_on — Function
y = is_Gz_on(x::Sequence)

Tells if the sequence seq has elements with GR active in z direction.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GRz in the sequence is active
source

is_ADC_on

KomaMRIBase.is_ADC_on — Function
y = is_ADC_on(x::Sequence)
-y = is_ADC_on(x::Sequence, t::Union{Array{Float64,1}, Array{Float64,2}})

Tells if the sequence seq has elements with ADC active, or active during time t.

Arguments

  • x: (::Sequence) sequence struct
  • t: (::Union{Array{Float64,1}, Array{Float64,2}}, [s]) time to check

Returns

  • y: (::Bool) boolean that tells whether or not the ADC in the sequence is active
source

get_samples

KomaMRIBase.get_samples — Function
samples = get_samples(seq::Sequence; off_val=0, max_rf_samples=Inf)

Returns the samples of the events in seq.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • off_val: (::Number, =0) offset value for amplitude. Typically used to hide points in plots by setting it to Inf
  • max_rf_samples: (::Integer, =Inf) maximum number of samples for the RF struct

Returns

  • samples: (::NamedTuple) contains samples for gx, gy, gz, rf, and adc events. Each event, represented by e::NamedTuple, includes time samples (e.t) and amplitude samples (e.A)
source

get_adc_sampling_times

KomaMRIBase.get_adc_sampling_times — Function
times = get_adc_sampling_times(seq)

Returns an array of times when the samples of the sequence seq are acquired.

Arguments

  • seq: (::Sequence) sequence struct

Returns

  • times: (::Vector{Float64}, [s]) time array when samples are acquired
source

get_adc_phase_compensation

KomaMRIBase.get_adc_phase_compensation — Function
comp = get_adc_phase_compensation(seq)

Returns an array of phase compensation factors, $\exp(-\mathrm{i}\varphi)$, which are used to compensate the acquired signal $S$ by applying the operation $S_{\mathrm{comp}} = S \exp(-\mathrm{i}\varphi)$ after the simulation. This compensation is necessary because the signal typically exhibits a phase offset of $\varphi$ following RF excitation with a phase of $\varphi$. Such pulses are commonly employed in sequences involving RF spoiling.

Arguments

  • seq: (::Sequence) sequence struct

Returns

  • comp: (::Vector{Complex}, [rad]) array of phase compensations for every acquired sample
source

get_block_start_times

KomaMRIBase.get_block_start_times — Function
T0 = get_block_start_times(seq::Sequence)

Returns a vector containing the start times of blocks in a sequence. The initial time is always zero, and the final time corresponds to the duration of the sequence.

Arguments

  • seq: (::Sequence) Sequence struct

Returns

  • T0: (::Vector, [s]) start times of the blocks in a sequence
source

DiscreteSequence

KomaMRIBase.DiscreteSequence — Type
seqd = DiscreteSequence(Gx, Gy, Gz, B1, Δf, ADC, t, Δt)

A sampled version of a Sequence struct, containing vectors for event amplitudes at specified times. DiscreteSequence is the struct used for simulation.

Arguments

  • Gx: (::AbstractVector{T<:Real}, [T/m]) x-gradient vector
  • Gy: (::AbstractVector{T<:Real}, [T/m]) y-gradient vector
  • Gz: (::AbstractVector{T<:Real}, [T/m]) z-gradient vector
  • B1: (::AbstractVector{Complex{T<:Real}}, [T]) RF amplitude vector
  • Δf: (::AbstractVector{T<:Real}, [Hz]) RF carrier frequency displacement vector
  • ADC: (::AbstractVector{Bool}) ADC sample vector
  • t: (::AbstractVector{T<:Real}, [s]) time vector
  • Δt: (::AbstractVector{T<:Real}, [s]) delta time vector

Returns

  • seqd: (::DiscreteSequence) DiscreteSequence struct
source

discretize

KomaMRIBase.discretize — Function
seqd = discretize(seq::Sequence; sampling_params=default_sampling_params())

This function returns a sampled Sequence struct with RF and gradient time refinements based on simulation parameters.

Arguments

  • seq: (::Sequence) sequence

Keywords

  • sampling_params: (::Dict{String, Any}, =default_sampling_params()) sampling parameter dictionary

Returns

  • seqd: (::DiscreteSequence) DiscreteSequence struct
source

Sampling Miscellaneous

trapz

KomaMRIBase.trapz — Function
y = trapz(Δt, x)

Trapezoidal integration for every spin of a phantom.

Note

In practice, this function is used to integrate (Gx * x + Gy * y + Gz * z) * Δt for all the spins. NΔt is the length of Δt. Ns stands for the number of spins of a phantom. x is a matrix which rows represents different spins and columns are different times and the elements are the field Gx * x + Gy * y + Gz * z values.

Arguments

  • Δt: (1 x NΔt ::Matrix{Float64}, [s]) delta time 1-row array
  • x: (Ns x (NΔt+1) ::Matrix{Float64}, [T]) magnitude of the field Gx * x + Gy * y + Gz * z

Returns

  • y: (Ns x 1 ::Matrix{Float64}, [T*s]) vector where every element is the integral of (Gx * x + Gy * y + Gz * z) * Δt for every spin of a phantom
source

cumtrapz

KomaMRIBase.cumtrapz — Function
y = cumtrapz(Δt, x)

Trapezoidal cumulative integration over time for every spin of a phantom.

Arguments

  • Δt: (1 x NΔt ::Matrix{Float64}, [s]) delta time 1-row array
  • x: (Ns x (NΔt+1) ::Matrix{Float64}, [T]) magnitude of the field Gx * x + Gy * y + Gz * z

Returns

  • y: (Ns x NΔt ::Matrix{Float64}, [T*s]) matrix where every column is the cumulative integration over time of (Gx * x + Gy * y + Gz * z) * Δt for every spin of a phantom
source

kfoldperm

KomaMRIBase.kfoldperm — Function
array_of_ranges = kfoldperm(N, k; breaks=[])

Divides a list of indices from 1 to N into k groups.

Arguments

  • N: (::Integer) number of elements to be ordered
  • k: (::Integer) number of groups to divide the N elements.

Keywords

  • breaks: (::Vector{<:Integer}, =[]) array of indices where predefined breakpoints are placed.

Returns

  • array_of_ranges: (::Vector{UnitRange{<:Integer}}) array containing ranges of different groups. The target is k groups, but this could increase by adding elements to the breaks input array
source

ampl

KomaMRIBase.ampl — Function
A = ampl(g::Grad)
+y = dur(x::Array{RF,2})

Duration time in [s] of RF struct or RF array.

Arguments

  • x: (::RF or ::Array{RF,1} or ::Array{RF,2}) RF struct or RF array

Returns

  • y: (::Float64, [s]) duration of the RF struct or RF array
source
T = dur(x::Sequence)

The total duration of the sequence in [s].

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • T: (::Real, [s]) total duration of the sequence
source

rotx

KomaMRIBase.rotx — Function
Rx = rotx(θ::Real)

Rotates vector counter-clockwise with respect to the x-axis.

Arguments

  • θ: (::Real, [rad]) rotation angle

Returns

  • Rx: (::Matrix{Int64}) rotation matrix
source

roty

KomaMRIBase.roty — Function
Ry = roty(θ::Real)

Rotates vector counter-clockwise with respect to the y-axis.

Arguments

  • θ: (::Real, [rad]) rotation angle

Returns

  • Ry: (::Matrix{Int64}) rotation matrix
source

rotz

KomaMRIBase.rotz — Function
Rz = rotz(θ::Real)

Rotates vector counter-clockwise with respect to the z-axis.

Arguments

  • θ: (::Real, [rad]) rotation angle

Returns

  • Rz: (::Matrix{Int64}) rotation matrix
source

get_Mk

KomaMRIBase.get_Mk — Function
Mk, Mk_adc = get_Mk(seq::Sequence, k; Δt=1, skip_rf=zeros(Bool, sum(is_RF_on.(seq))))

Computes the $k$th-order moment of the Sequence seq given by the formula $\int_0^T t^k G(t) dt$.

Arguments

  • seq: (::Sequence) Sequence struct
  • k: (::Integer) order of the moment to be computed
  • Δt: (::Real, =1, [s]) nominal delta time separation between two time samples for ADC acquisition and Gradients
  • skip_rf: (::Vector{Bool}, =zeros(Bool, sum(is_RF_on.(seq)))) boolean vector which indicates whether to skip the computation for resetting the integral for excitation or refocusing RF type

Returns

  • Mk: (3-column ::Matrix{Real}) $k$th-order moment
  • Mk_adc: (3-column ::Matrix{Real}) $k$th-order moment sampled at ADC times
source

get_kspace

KomaMRIBase.get_kspace — Function

Computes the k-space trajectory of the Sequence seq. Refer to get_Mk and get_M0

source

get_M0

KomaMRIBase.get_M0 — Function

Computes the zero-order moment of the Sequence seq. Refer to get_Mk and get_kspace

source

get_M1

KomaMRIBase.get_M1 — Function

Computes the 1st-order moment of the Sequence seq. Refer to get_Mk

source

get_M2

KomaMRIBase.get_M2 — Function

Computes the 2nd-order moment of the Sequence seq. Refer to get_Mk

source

get_flip_angles

KomaMRIBase.get_flip_angles — Function
y = get_flip_angles(x::Sequence)

Returns all the flip angles of the RF pulses in the sequence x.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Vector{Float64}, [deg]) flip angles
source

is_RF_on

KomaMRIBase.is_RF_on — Function
y = is_RF_on(x::Sequence)
+y = is_RF_on(x::Sequence, t::Vector{Float64})

Tells if the sequence seq has elements with RF active, or active during time t.

Arguments

  • x: (::Sequence) Sequence struct
  • t: (::Vector{Float64}, [s]) time to check

Returns

  • y: (::Bool) boolean that tells whether or not the RF in the sequence is active
source

is_GR_on

KomaMRIBase.is_GR_on — Function
y = is_GR_on(x::Sequence)

Tells if the sequence seq has elements with GR active.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GR in the sequence is active
source

is_Gx_on

KomaMRIBase.is_Gx_on — Function
y = is_Gx_on(x::Sequence)

Tells if the sequence seq has elements with GR active in x direction.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GRx in the sequence is active
source

is_Gy_on

KomaMRIBase.is_Gy_on — Function
y = is_Gy_on(x::Sequence)

Tells if the sequence seq has elements with GR active in y direction.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GRy in the sequence is active
source

is_Gz_on

KomaMRIBase.is_Gz_on — Function
y = is_Gz_on(x::Sequence)

Tells if the sequence seq has elements with GR active in z direction.

Arguments

  • x: (::Sequence) Sequence struct

Returns

  • y: (::Bool) boolean that tells whether or not the GRz in the sequence is active
source

is_ADC_on

KomaMRIBase.is_ADC_on — Function
y = is_ADC_on(x::Sequence)
+y = is_ADC_on(x::Sequence, t::Union{Array{Float64,1}, Array{Float64,2}})

Tells if the sequence seq has elements with ADC active, or active during time t.

Arguments

  • x: (::Sequence) sequence struct
  • t: (::Union{Array{Float64,1}, Array{Float64,2}}, [s]) time to check

Returns

  • y: (::Bool) boolean that tells whether or not the ADC in the sequence is active
source

get_samples

KomaMRIBase.get_samples — Function
samples = get_samples(seq::Sequence; off_val=0, max_rf_samples=Inf)

Returns the samples of the events in seq.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • off_val: (::Number, =0) offset value for amplitude. Typically used to hide points in plots by setting it to Inf
  • max_rf_samples: (::Integer, =Inf) maximum number of samples for the RF struct

Returns

  • samples: (::NamedTuple) contains samples for gx, gy, gz, rf, and adc events. Each event, represented by e::NamedTuple, includes time samples (e.t) and amplitude samples (e.A)
source

get_adc_sampling_times

KomaMRIBase.get_adc_sampling_times — Function
times = get_adc_sampling_times(seq)

Returns an array of times when the samples of the sequence seq are acquired.

Arguments

  • seq: (::Sequence) sequence struct

Returns

  • times: (::Vector{Float64}, [s]) time array when samples are acquired
source

get_adc_phase_compensation

KomaMRIBase.get_adc_phase_compensation — Function
comp = get_adc_phase_compensation(seq)

Returns an array of phase compensation factors, $\exp(-\mathrm{i}\varphi)$, which are used to compensate the acquired signal $S$ by applying the operation $S_{\mathrm{comp}} = S \exp(-\mathrm{i}\varphi)$ after the simulation. This compensation is necessary because the signal typically exhibits a phase offset of $\varphi$ following RF excitation with a phase of $\varphi$. Such pulses are commonly employed in sequences involving RF spoiling.

Arguments

  • seq: (::Sequence) sequence struct

Returns

  • comp: (::Vector{Complex}, [rad]) array of phase compensations for every acquired sample
source

get_block_start_times

KomaMRIBase.get_block_start_times — Function
T0 = get_block_start_times(seq::Sequence)

Returns a vector containing the start times of blocks in a sequence. The initial time is always zero, and the final time corresponds to the duration of the sequence.

Arguments

  • seq: (::Sequence) Sequence struct

Returns

  • T0: (::Vector, [s]) start times of the blocks in a sequence
source

DiscreteSequence

KomaMRIBase.DiscreteSequence — Type
seqd = DiscreteSequence(Gx, Gy, Gz, B1, Δf, ADC, t, Δt)

A sampled version of a Sequence struct, containing vectors for event amplitudes at specified times. DiscreteSequence is the struct used for simulation.

Arguments

  • Gx: (::AbstractVector{T<:Real}, [T/m]) x-gradient vector
  • Gy: (::AbstractVector{T<:Real}, [T/m]) y-gradient vector
  • Gz: (::AbstractVector{T<:Real}, [T/m]) z-gradient vector
  • B1: (::AbstractVector{Complex{T<:Real}}, [T]) RF amplitude vector
  • Δf: (::AbstractVector{T<:Real}, [Hz]) RF carrier frequency displacement vector
  • ADC: (::AbstractVector{Bool}) ADC sample vector
  • t: (::AbstractVector{T<:Real}, [s]) time vector
  • Δt: (::AbstractVector{T<:Real}, [s]) delta time vector

Returns

  • seqd: (::DiscreteSequence) DiscreteSequence struct
source

discretize

KomaMRIBase.discretize — Function
seqd = discretize(seq::Sequence; sampling_params=default_sampling_params())

This function returns a sampled Sequence struct with RF and gradient time refinements based on simulation parameters.

Arguments

  • seq: (::Sequence) sequence

Keywords

  • sampling_params: (::Dict{String, Any}, =default_sampling_params()) sampling parameter dictionary

Returns

  • seqd: (::DiscreteSequence) DiscreteSequence struct
source

Sampling Miscellaneous

trapz

KomaMRIBase.trapz — Function
y = trapz(Δt, x)

Trapezoidal integration for every spin of a phantom.

Note

In practice, this function is used to integrate (Gx * x + Gy * y + Gz * z) * Δt for all the spins. NΔt is the length of Δt. Ns stands for the number of spins of a phantom. x is a matrix which rows represents different spins and columns are different times and the elements are the field Gx * x + Gy * y + Gz * z values.

Arguments

  • Δt: (1 x NΔt ::Matrix{Float64}, [s]) delta time 1-row array
  • x: (Ns x (NΔt+1) ::Matrix{Float64}, [T]) magnitude of the field Gx * x + Gy * y + Gz * z

Returns

  • y: (Ns x 1 ::Matrix{Float64}, [T*s]) vector where every element is the integral of (Gx * x + Gy * y + Gz * z) * Δt for every spin of a phantom
source

cumtrapz

KomaMRIBase.cumtrapz — Function
y = cumtrapz(Δt, x)

Trapezoidal cumulative integration over time for every spin of a phantom.

Arguments

  • Δt: (1 x NΔt ::Matrix{Float64}, [s]) delta time 1-row array
  • x: (Ns x (NΔt+1) ::Matrix{Float64}, [T]) magnitude of the field Gx * x + Gy * y + Gz * z

Returns

  • y: (Ns x NΔt ::Matrix{Float64}, [T*s]) matrix where every column is the cumulative integration over time of (Gx * x + Gy * y + Gz * z) * Δt for every spin of a phantom
source

kfoldperm

KomaMRIBase.kfoldperm — Function
array_of_ranges = kfoldperm(N, k; breaks=[])

Divides a list of indices from 1 to N into k groups.

Arguments

  • N: (::Integer) number of elements to be ordered
  • k: (::Integer) number of groups to divide the N elements.

Keywords

  • breaks: (::Vector{<:Integer}, =[]) array of indices where predefined breakpoints are placed.

Returns

  • array_of_ranges: (::Vector{UnitRange{<:Integer}}) array containing ranges of different groups. The target is k groups, but this could increase by adding elements to the breaks input array
source

ampl

KomaMRIBase.ampl — Function
A = ampl(g::Grad)
 A = ampl(r::RF)
-A = ampl(d::ADC)

Get the theoretical amplitudes for Grad, RF or ADC structs.

Arguments

  • gr: (::Grad) Gradient struct
  • rf: (::RF) RF struct
  • adc: (::ADC) ADC truct

Returns

  • A: (::Vector{Number}) vector with the amplitude theoretical points
source

time

KomaMRIBase.time — Function
t = time(gr::Grad)
+A = ampl(d::ADC)

Get the theoretical amplitudes for Grad, RF or ADC structs.

Arguments

  • gr: (::Grad) Gradient struct
  • rf: (::RF) RF struct
  • adc: (::ADC) ADC truct

Returns

  • A: (::Vector{Number}) vector with the amplitude theoretical points
source

time

KomaMRIBase.time — Function
t = time(gr::Grad)
 t = time(rf::RF)
-t = time(adc::ADC)

Get the theoretical times for Grad, RF or ADC structs.

Arguments

  • gr: (::Grad) Gradient struct
  • rf: (::RF) RF struct
  • adc: (::ADC) ADC truct

Returns

  • t: (::Vector{Number}) vector with the time theoretical points
source

Prebuilt Sequence Building Blocks

PulseDesigner

KomaMRIBase.PulseDesigner — Module
PulseDesigner

A module to define different pulse sequences.

source

PulseDesigner.RF_hard

KomaMRIBase.PulseDesigner.RF_hard — Function
seq = RF_hard(B1, T, sys; G=[0, 0, 0], Δf=0)

Returns a sequence with a RF excitation pulse.

Arguments

  • B1: (::Number, [T]) RF pulse amplitude
  • T: (::Real, [s]) RF pulse duration
  • sys: (::Scanner) Scanner struct

Keywords

  • G: (::Vector{Real}, =[0, 0, 0], [T/m]) gradient amplitudes for x, y, z
  • Δf: (::Real, =0, [Hz]) RF pulse carrier frequency displacement

Returns

  • seq: (::Sequence) Sequence struct with a RF pulse

Examples

julia> sys = Scanner(); durRF = π / 2 / (2π * γ * sys.B1);
+t = time(adc::ADC)

Get the theoretical times for Grad, RF or ADC structs.

Arguments

  • gr: (::Grad) Gradient struct
  • rf: (::RF) RF struct
  • adc: (::ADC) ADC truct

Returns

  • t: (::Vector{Number}) vector with the time theoretical points
source

Prebuilt Sequence Building Blocks

PulseDesigner

KomaMRIBase.PulseDesigner — Module
PulseDesigner

A module to define different pulse sequences.

source

PulseDesigner.RF_hard

KomaMRIBase.PulseDesigner.RF_hard — Function
seq = RF_hard(B1, T, sys; G=[0, 0, 0], Δf=0)

Returns a sequence with a RF excitation pulse.

Arguments

  • B1: (::Number, [T]) RF pulse amplitude
  • T: (::Real, [s]) RF pulse duration
  • sys: (::Scanner) Scanner struct

Keywords

  • G: (::Vector{Real}, =[0, 0, 0], [T/m]) gradient amplitudes for x, y, z
  • Δf: (::Real, =0, [Hz]) RF pulse carrier frequency displacement

Returns

  • seq: (::Sequence) Sequence struct with a RF pulse

Examples

julia> sys = Scanner(); durRF = π / 2 / (2π * γ * sys.B1);
 
 julia> seq = PulseDesigner.RF_hard(sys.B1, durRF, sys);
 
-julia> plot_seq(seq)
source

PulseDesigner.RF_sinc

KomaMRIBase.PulseDesigner.RF_sinc — Function
seq = RF_sinc(B1, T, sys; G=[0, 0, 0], Δf=0, a=0.46, TBP=4)

Returns a sequence with a RF sinc waveform.

References

  • Matt A. Bernstein, Kevin F. King, Xiaohong Joe Zhou, Chapter 2 - Radiofrequency Pulse

Shapes, Handbook of MRI Pulse Sequences, 2004, Pages 35-66, https://doi.org/10.1016/B978-012092861-3/50006-6.

Arguments

  • B1: (::Number, [T]) RF sinc amplitude
  • T: (::Real, [s]) RF sinc duration
  • sys: (::Scanner) Scanner struct

Keywords

  • G: (::Vector{Real}, =[0, 0, 0], [T/m]) gradient amplitudes for x, y, z
  • Δf: (::Real, =0, [Hz]) RF pulse carrier frequency displacement
  • a: (::Real, =0.46) height appodization window parameter
  • TBP: (::Real, =4) width appodization window parameter

Returns

  • seq: (::Sequence) Sequence struct with a RF pulse

Examples

julia> sys = Scanner(); durRF = π / 2 / (2π * γ * sys.B1);
+julia> plot_seq(seq)
source

PulseDesigner.RF_sinc

KomaMRIBase.PulseDesigner.RF_sinc — Function
seq = RF_sinc(B1, T, sys; G=[0, 0, 0], Δf=0, a=0.46, TBP=4)

Returns a sequence with a RF sinc waveform.

References

  • Matt A. Bernstein, Kevin F. King, Xiaohong Joe Zhou, Chapter 2 - Radiofrequency Pulse

Shapes, Handbook of MRI Pulse Sequences, 2004, Pages 35-66, https://doi.org/10.1016/B978-012092861-3/50006-6.

Arguments

  • B1: (::Number, [T]) RF sinc amplitude
  • T: (::Real, [s]) RF sinc duration
  • sys: (::Scanner) Scanner struct

Keywords

  • G: (::Vector{Real}, =[0, 0, 0], [T/m]) gradient amplitudes for x, y, z
  • Δf: (::Real, =0, [Hz]) RF pulse carrier frequency displacement
  • a: (::Real, =0.46) height appodization window parameter
  • TBP: (::Real, =4) width appodization window parameter

Returns

  • seq: (::Sequence) Sequence struct with a RF pulse

Examples

julia> sys = Scanner(); durRF = π / 2 / (2π * γ * sys.B1);
 
 julia> seq = PulseDesigner.RF_sinc(sys.B1, durRF, sys);
 
-julia> plot_seq(seq)
source

PulseDesigner.EPI

KomaMRIBase.PulseDesigner.EPI — Function
seq = EPI(FOV::Real, N::Integer, sys::Scanner)

Returns a sequence with EPI gradients.

Arguments

  • FOV: (::Real, [m]) field of view
  • N: (::Integer) number of pixels in the x and y axis
  • sys: (::Scanner) Scanner struct

Returns

  • seq: (::Sequence) Sequence struct with EPI gradients

Examples

julia> sys, FOV, N = Scanner(), 23e-2, 101
+julia> plot_seq(seq)
source

PulseDesigner.EPI

KomaMRIBase.PulseDesigner.EPI — Function
seq = EPI(FOV::Real, N::Integer, sys::Scanner)

Returns a sequence with EPI gradients.

Arguments

  • FOV: (::Real, [m]) field of view
  • N: (::Integer) number of pixels in the x and y axis
  • sys: (::Scanner) Scanner struct

Returns

  • seq: (::Sequence) Sequence struct with EPI gradients

Examples

julia> sys, FOV, N = Scanner(), 23e-2, 101
 
 julia> seq = PulseDesigner.EPI(FOV, N, sys)
 
 julia> plot_seq(seq)
 
-julia> plot_kspace(seq)
source

PulseDesigner.radial_base

KomaMRIBase.PulseDesigner.radial_base — Function
seq = radial_base(FOV::Real, Nr::Integer, sys::Scanner)

Returns a sequence with radial gradients for a single trajectory.

Arguments

  • FOV: (::Real, [m]) field of view
  • N: (::Integer) number of pixels along the diameter
  • sys: (::Scanner) Scanner struct

Returns

  • seq: (::Sequence) Sequence struct of a single radial trajectory

Examples

julia> sys, FOV, N = Scanner(), 23e-2, 101
+julia> plot_kspace(seq)
source

PulseDesigner.radial_base

KomaMRIBase.PulseDesigner.radial_base — Function
seq = radial_base(FOV::Real, Nr::Integer, sys::Scanner)

Returns a sequence with radial gradients for a single trajectory.

Arguments

  • FOV: (::Real, [m]) field of view
  • N: (::Integer) number of pixels along the diameter
  • sys: (::Scanner) Scanner struct

Returns

  • seq: (::Sequence) Sequence struct of a single radial trajectory

Examples

julia> sys, FOV, N = Scanner(), 23e-2, 101
 
 julia> seq = PulseDesigner.radial_base(FOV, N, sys)
 
 julia> plot_seq(seq)
 
-julia> plot_kspace(seq)
source

PulseDesigner.spiral_base

KomaMRIBase.PulseDesigner.spiral_base — Function
spiral = spiral_base(FOV, N, sys; S0=sys.Smax*2/3, Nint=8, λ=Nint/FOV, BW=60e3)

Definition of a spiral base sequence.

References

  • Glover, G.H. (1999), Simple analytic spiral K-space algorithm. Magn. Reson. Med.,

42: 412-415. https://doi.org/10.1002/(SICI)1522-2594(199908)42:2<412::AID-MRM25>3.0.CO;2-U

Arguments

  • FOV: (::Real, [m]) field of view
  • N: (::Integer) number of pixels along the radious
  • sys: (::Scanner) Scanner struct

Keywords

  • S0: (::Vector{Real}, =sys.Smax*2/3, [T/m/s]) slew rate reference
  • Nint: (::Integer, =8) number of interleaves
  • λ: (::Real, =Nint/FOV, [1/m]) kspace spiral parameter
  • BW: (::Real, =60e3, [Hz]) adquisition parameter

Returns

  • spiral: (::Function) function that returns a Sequence struct when evaluated

Examples

julia> sys, FOV, N = Scanner(), 23e-2, 101
+julia> plot_kspace(seq)
source

PulseDesigner.spiral_base

KomaMRIBase.PulseDesigner.spiral_base — Function
spiral = spiral_base(FOV, N, sys; S0=sys.Smax*2/3, Nint=8, λ=Nint/FOV, BW=60e3)

Definition of a spiral base sequence.

References

  • Glover, G.H. (1999), Simple analytic spiral K-space algorithm. Magn. Reson. Med.,

42: 412-415. https://doi.org/10.1002/(SICI)1522-2594(199908)42:2<412::AID-MRM25>3.0.CO;2-U

Arguments

  • FOV: (::Real, [m]) field of view
  • N: (::Integer) number of pixels along the radious
  • sys: (::Scanner) Scanner struct

Keywords

  • S0: (::Vector{Real}, =sys.Smax*2/3, [T/m/s]) slew rate reference
  • Nint: (::Integer, =8) number of interleaves
  • λ: (::Real, =Nint/FOV, [1/m]) kspace spiral parameter
  • BW: (::Real, =60e3, [Hz]) adquisition parameter

Returns

  • spiral: (::Function) function that returns a Sequence struct when evaluated

Examples

julia> sys, FOV, N = Scanner(), 23e-2, 101
 
 julia> spiral = PulseDesigner.spiral_base(FOV, N, sys)
 
 julia> seq = spiral(0)
 
-julia> plot_seq(seq)
source

PulseDesigner.EPI_example

KomaMRIBase.PulseDesigner.EPI_example — Function
seq = EPI_example(; sys=Scanner())

Returns a sequence suitable for acquiring the 2D brain example in the provided examples.

Keywords

  • sys: (::Scanner) Scanner struct

Returns

  • seq: (::Sequence) EPI example Sequence struct

Examples

julia> seq = PulseDesigner.EPI_example();
+julia> plot_seq(seq)
source

PulseDesigner.EPI_example

KomaMRIBase.PulseDesigner.EPI_example — Function
seq = EPI_example(; sys=Scanner())

Returns a sequence suitable for acquiring the 2D brain example in the provided examples.

Keywords

  • sys: (::Scanner) Scanner struct

Returns

  • seq: (::Sequence) EPI example Sequence struct

Examples

julia> seq = PulseDesigner.EPI_example();
 
-julia> plot_seq(seq)
source

Input/Output

read_seq

KomaMRIFiles.read_seq — Function
seq = read_seq(filename)

Returns the Sequence struct from a Pulseq file with .seq extension.

Arguments

  • filename: (::String) absolute or relative path of the sequence file .seq

Returns

  • seq: (::Sequence) Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_seq(seq)
source

Input/Output

read_seq

KomaMRIFiles.read_seq — Function
seq = read_seq(filename)

Returns the Sequence struct from a Pulseq file with .seq extension.

Arguments

  • filename: (::String) absolute or relative path of the sequence file .seq

Returns

  • seq: (::Sequence) Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_seq(seq)
source

write_seq

KomaMRIFiles.write_seq — Function
write_seq(seq::Sequence, filename::String)

Writes a .seq file for a given sequence seq y the location filename

source

read_phantom_jemris

KomaMRIFiles.read_phantom_jemris — Function
obj = read_phantom_jemris(filename)

Returns the Phantom struct from a JEMRIS phantom file .h5.

Arguments

  • filename: (::String) the absolute or relative path of the phantom file .h5

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj_file = joinpath(dirname(pathof(KomaMRI)), "../examples/2.phantoms/brain.h5")
+julia> plot_seq(seq)
source

write_seq

KomaMRIFiles.write_seq — Function
write_seq(seq::Sequence, filename::String)

Writes a .seq file for a given sequence seq y the location filename

source

read_phantom_jemris

KomaMRIFiles.read_phantom_jemris — Function
obj = read_phantom_jemris(filename)

Returns the Phantom struct from a JEMRIS phantom file .h5.

Arguments

  • filename: (::String) the absolute or relative path of the phantom file .h5

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj_file = joinpath(dirname(pathof(KomaMRI)), "../examples/2.phantoms/brain.h5")
 
 julia> obj = read_phantom_jemris(obj_file)
 
-julia> plot_phantom_map(obj, :ρ)
source

read_phantom_MRiLab

KomaMRIFiles.read_phantom_MRiLab — Function
obj = read_phantom_MRiLab(filename)

Returns the Phantom struct from a MRiLab phantom file .mat.

Arguments

  • filename: (::String) the absolute or relative path of the phantom file .mat

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj_file = joinpath(dirname(pathof(KomaMRI)), "../examples/2.phantoms/brain.mat")
+julia> plot_phantom_map(obj, :ρ)
source

read_phantom_MRiLab

KomaMRIFiles.read_phantom_MRiLab — Function
obj = read_phantom_MRiLab(filename)

Returns the Phantom struct from a MRiLab phantom file .mat.

Arguments

  • filename: (::String) the absolute or relative path of the phantom file .mat

Returns

  • obj: (::Phantom) Phantom struct

Examples

julia> obj_file = joinpath(dirname(pathof(KomaMRI)), "../examples/2.phantoms/brain.mat")
 
 julia> obj = read_phantom_MRiLab(obj_file)
 
-julia> plot_phantom_map(obj, :ρ)
source

Functor Functions

f32

KomaMRICore.f32 — Function
f32(m)

Converts the eltype of model's parameters to Float32 Recurses into structs marked with @functor.

See also f64.

source

f64

KomaMRICore.f64 — Function
f64(m)

Converts the eltype of model's parameters to Float64 (which is Koma's default).. Recurses into structs marked with @functor.

See also f32.

source

cpu

KomaMRICore.cpu — Function
cpu(x)

Tries to move object to CPU. Inspired by Flux's cpu function.

This works for functions, and any struct marked with @functor.

See also gpu.

Examples

x = x |> cpu
source

gpu

KomaMRICore.gpu — Function
gpu(x)

Tries to move x to the current GPU device. Inspired by Flux's gpu function.

This works for functions, and any struct marked with @functor.

Use cpu to copy back to ordinary Arrays.

See also f32 and f64 to change element type only.

Examples

x = x |> gpu
source

Simulation

default_sim_params

KomaMRICore.default_sim_params — Function
sim_params = default_sim_params(sim_params=Dict{String,Any}())

This function returns a dictionary containing default simulation parameters while also allowing the user to define some of them.

Arguments

  • sim_params: (::Dict{String,Any}, =Dict{String,Any}()) user-defined dictionary with simulation parameters. The following lists its keys along with their possible values:
    • "return_type": defines the output of the simulate function. Possible values are "raw", "mat", and "state", corresponding to outputting a MRIReco RawAcquisitionData, the signal values, and the last magnetization state of the simulation, respectively
    • "sim_method": defines the type of simulation. The default value is Bloch(), but you can alternatively use the BlochDict() simulation method. Moreover, you have the flexibility to create your own methods without altering the KomaMRI source code
    • "Δt": raster time for gradients
    • "Δt_rf": raster time for RFs
    • "precision": defines the floating-point simulation precision. You can choose between "f32" and "f64" to use Float32 and Float64 primitive types, respectively. It's important to note that, especially for GPU operations, using "f32" is generally much faster
    • "Nblocks": divides the simulation into a specified number of time blocks. This parameter is designed to conserve RAM resources, as KomaMRI computes a series of simulations consecutively, each with the specified number of blocks determined by the value of "Nblocks"
    • "Nthreads": divides the Phantom into a specified number of threads. Because spins are modeled independently of each other, KomaMRI can solve simulations in parallel threads, speeding up the execution time
    • "gpu": is a boolean that determines whether to use GPU or CPU hardware resources, as long as they are available on the host computer
    • "gpu_device": sets the index ID of the available GPU in the host computer

Returns

  • sim_params: (::Dict{String,Any}) dictionary with simulation parameters
source

simulate

KomaMRICore.simulate — Function
out = simulate(obj::Phantom, seq::Sequence, sys::Scanner; sim_params, w)

Returns the raw signal or the last state of the magnetization according to the value of the "return_type" key of the sim_params dictionary.

Arguments

  • obj: (::Phantom) Phantom struct
  • seq: (::Sequence) Sequence struct
  • sys: (::Scanner) Scanner struct

Keywords

  • sim_params: (::Dict{String,Any}, =Dict{String,Any}()) simulation parameter dictionary
  • w: (::Blink.AtomShell.Window, =nothing) the window within which to display a progress bar in the Blink Window UI. If this variable is anything other than 'nothing', the progress bar will be considered

Returns

  • out: (::Vector{Complex} or ::SpinStateRepresentation or ::RawAcquisitionData) depending on whether "return_type" is "mat", "state" or "raw" (default), respectively

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/3.koma_paper/comparison_accuracy/sequences/EPI/epi_100x100_TE100_FOV230.seq");
+julia> plot_phantom_map(obj, :ρ)
source

Functor Functions

f32

KomaMRICore.f32 — Function
f32(m)

Converts the eltype of model's parameters to Float32 Recurses into structs marked with @functor.

See also f64.

source

f64

KomaMRICore.f64 — Function
f64(m)

Converts the eltype of model's parameters to Float64 (which is Koma's default).. Recurses into structs marked with @functor.

See also f32.

source

cpu

KomaMRICore.cpu — Function
cpu(x)

Tries to move object to CPU. Inspired by Flux's cpu function.

This works for functions, and any struct marked with @functor.

See also gpu.

Examples

x = x |> cpu
source

gpu

KomaMRICore.gpu — Function
gpu(x)

Tries to move x to the current GPU device. Inspired by Flux's gpu function.

This works for functions, and any struct marked with @functor.

Use cpu to copy back to ordinary Arrays.

See also f32 and f64 to change element type only.

Examples

x = x |> gpu
source

Simulation

default_sim_params

KomaMRICore.default_sim_params — Function
sim_params = default_sim_params(sim_params=Dict{String,Any}())

This function returns a dictionary containing default simulation parameters while also allowing the user to define some of them.

Arguments

  • sim_params: (::Dict{String,Any}, =Dict{String,Any}()) user-defined dictionary with simulation parameters. The following lists its keys along with their possible values:
    • "return_type": defines the output of the simulate function. Possible values are "raw", "mat", and "state", corresponding to outputting a MRIReco RawAcquisitionData, the signal values, and the last magnetization state of the simulation, respectively
    • "sim_method": defines the type of simulation. The default value is Bloch(), but you can alternatively use the BlochDict() simulation method. Moreover, you have the flexibility to create your own methods without altering the KomaMRI source code
    • "Δt": raster time for gradients
    • "Δt_rf": raster time for RFs
    • "precision": defines the floating-point simulation precision. You can choose between "f32" and "f64" to use Float32 and Float64 primitive types, respectively. It's important to note that, especially for GPU operations, using "f32" is generally much faster
    • "Nblocks": divides the simulation into a specified number of time blocks. This parameter is designed to conserve RAM resources, as KomaMRI computes a series of simulations consecutively, each with the specified number of blocks determined by the value of "Nblocks"
    • "Nthreads": divides the Phantom into a specified number of threads. Because spins are modeled independently of each other, KomaMRI can solve simulations in parallel threads, speeding up the execution time
    • "gpu": is a boolean that determines whether to use GPU or CPU hardware resources, as long as they are available on the host computer
    • "gpu_device": sets the index ID of the available GPU in the host computer

Returns

  • sim_params: (::Dict{String,Any}) dictionary with simulation parameters
source

simulate

KomaMRICore.simulate — Function
out = simulate(obj::Phantom, seq::Sequence, sys::Scanner; sim_params, w)

Returns the raw signal or the last state of the magnetization according to the value of the "return_type" key of the sim_params dictionary.

Arguments

  • obj: (::Phantom) Phantom struct
  • seq: (::Sequence) Sequence struct
  • sys: (::Scanner) Scanner struct

Keywords

  • sim_params: (::Dict{String,Any}, =Dict{String,Any}()) simulation parameter dictionary
  • w: (::Blink.AtomShell.Window, =nothing) the window within which to display a progress bar in the Blink Window UI. If this variable is anything other than 'nothing', the progress bar will be considered

Returns

  • out: (::Vector{Complex} or ::SpinStateRepresentation or ::RawAcquisitionData) depending on whether "return_type" is "mat", "state" or "raw" (default), respectively

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/3.koma_paper/comparison_accuracy/sequences/EPI/epi_100x100_TE100_FOV230.seq");
 
 julia> sys, obj, seq = Scanner(), brain_phantom2D(), read_seq(seq_file)
 
 julia> raw = simulate(obj, seq, sys)
 
-julia> plot_signal(raw)
source

simulate_slice_profile

KomaMRICore.simulate_slice_profile — Function
mag = simulate_slice_profile(seq; z, sim_params)

Returns magnetization of spins distributed along z after running the Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • z: (=range(-2e-2,2e-2,200)) range for the z axis
  • sim_params: (::Dict{String, Any}, =Dict{String,Any}("Δt_rf"=>1e-6)) dictionary with simulation parameters

Returns

  • mag: (::SpinStateRepresentation) final state of the magnetization vector
source

signal_to_raw_data

KomaMRICore.signal_to_raw_data — Function
raw = signal_to_raw_data(signal, seq; phantom_name, sys, sim_params)

Transforms the raw signal into a RawAcquisitionData struct (nearly equivalent to the ISMRMRD format) used for reconstruction with MRIReco.

Arguments

  • signal: (::Matrix{Complex}) raw signal matrix
  • seq: (::Sequence) Sequence struct

Keywords

  • phantom_name: (::String, ="Phantom") phantom name
  • sys: (::Scanner, =Scanner()) Scanner struct
  • sim_params: (::Dict{String, Any}, =Dict{String,Any}()) simulation parameter dictionary

Returns

  • raw: (::RawAcquisitionData) RawAcquisitionData struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/epi_se.seq")
+julia> plot_signal(raw)
source

simulate_slice_profile

KomaMRICore.simulate_slice_profile — Function
mag = simulate_slice_profile(seq; z, sim_params)

Returns magnetization of spins distributed along z after running the Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • z: (=range(-2e-2,2e-2,200)) range for the z axis
  • sim_params: (::Dict{String, Any}, =Dict{String,Any}("Δt_rf"=>1e-6)) dictionary with simulation parameters

Returns

  • mag: (::SpinStateRepresentation) final state of the magnetization vector
source

signal_to_raw_data

KomaMRICore.signal_to_raw_data — Function
raw = signal_to_raw_data(signal, seq; phantom_name, sys, sim_params)

Transforms the raw signal into a RawAcquisitionData struct (nearly equivalent to the ISMRMRD format) used for reconstruction with MRIReco.

Arguments

  • signal: (::Matrix{Complex}) raw signal matrix
  • seq: (::Sequence) Sequence struct

Keywords

  • phantom_name: (::String, ="Phantom") phantom name
  • sys: (::Scanner, =Scanner()) Scanner struct
  • sim_params: (::Dict{String, Any}, =Dict{String,Any}()) simulation parameter dictionary

Returns

  • raw: (::RawAcquisitionData) RawAcquisitionData struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/epi_se.seq")
 
 julia> sys, obj, seq = Scanner(), brain_phantom2D(), read_seq(seq_file)
 
@@ -110,50 +110,50 @@
 
 julia> raw = signal_to_raw_data(signal, seq)
 
-julia> plot_signal(raw)
source

Mag

KomaMRICore.Mag — Type
mag = Mag(xy::Complex, z::Real)

The Magnetization struct.

Arguments

  • xy: (::Complex{Float64}) magnetization of a spin in the xy plane
  • z: (::Real) magnetization of a spin in the z plane

Returns

  • mag: (::Mag) Magnetization struct
source

Simulation Miscellaneous

Spinor

KomaMRICore.Spinor — Type
spinor = Spinor(α, β)

Spinor(α, β) with Cayley-Klein parameters α and β. Based on "Introduction to the Shinnar-Le Roux algorithm", Patrick Le Roux (1995). A spinor is a way to represent 3D rotations, the underlying representation is a 2 X 2 complex unitary matrix ($\alpha,\beta\in\mathbb{C}$):

\[R=\left[\begin{array}{cc} +julia> plot_signal(raw)

source

Mag

KomaMRICore.Mag — Type
mag = Mag(xy::Complex, z::Real)

The Magnetization struct.

Arguments

  • xy: (::Complex{Float64}) magnetization of a spin in the xy plane
  • z: (::Real) magnetization of a spin in the z plane

Returns

  • mag: (::Mag) Magnetization struct
source

Simulation Miscellaneous

Spinor

KomaMRICore.Spinor — Type
spinor = Spinor(α, β)

Spinor(α, β) with Cayley-Klein parameters α and β. Based on "Introduction to the Shinnar-Le Roux algorithm", Patrick Le Roux (1995). A spinor is a way to represent 3D rotations, the underlying representation is a 2 X 2 complex unitary matrix ($\alpha,\beta\in\mathbb{C}$):

\[R=\left[\begin{array}{cc} \alpha & -\beta^{*}\\ \beta & \alpha^{*} -\end{array}\right],\]

with $|\alpha|^2+|\beta|^2 = 1$.

This later operates on the $2\times2$ representation of $(x,y,z)$ as follows $V^{+} = R V R^{*}$.

Arguments

  • α: (::Complex{Float64}) Cayley-Klein parameter α
  • β: (::Complex{Float64}) Cayley-Klein parameter β

Returns

  • spinor: (::Spinor) Spinor struct
source

Q

KomaMRICore.Q — Function
s = Q(φ, nxy, nz)

Spinor rotation matrix. Counter-clockwise rotation of φ with respect to the axis of rotation n=(nx, ny, nz).

Pauly, J., Le Roux, P., Nishimura, D., & Macovski, A. (1991). Parameter relations for the Shinnar-Le Roux selective excitation pulse design algorithm (NMR imaging). IEEE Transactions on Medical Imaging, 10(1), 53-65. doi:10.1109/42.75611

\[\varphi=-\gamma\Delta t\sqrt{\left|B_{1}\right|^{2}+\left(\boldsymbol{G}\cdot\boldsymbol{x} -\right)^{2}}=-\gamma\Delta t\left\Vert \boldsymbol{B}\right\Vert\]

\[\boldsymbol{n}=\boldsymbol{B}/\left\Vert \boldsymbol{B}\right\Vert\]

Arguments

  • φ: (::Real, [rad]) φ angle
  • nxy: (::Real) nxy factor
  • nz: (::Real) nz factor

Returns

  • s: (::Spinor) spinnor struct that represents the Q rotation matrix
source

Un

KomaMRICore.Un — Function

Rodrigues' formula: Rotation matrix that when applied rotates with respect to "n" in an angle θ anti clock-wise

source

Rx

KomaMRICore.Rx — Function
s = Rx(θ)

Spinor counter-clockwise rotation matrix with angle θ with respect to x-axis.

Arguments

  • θ: (::Real, [rad]) angle with respect to x-axis

Returns

  • s: (::Spinor) spinor struct that represents the Rx rotation matrix
source

Ry

KomaMRICore.Ry — Function
s = Ry(θ)

Spinor counter-clockwise rotation matrix with angle θ with respect to y-axis.

Arguments

  • θ: (::Real, [rad]) angle with respect to y-axis

Returns

  • s: (::Spinor) spinor struct that represents the Ry rotation matrix
source

Rz

KomaMRICore.Rz — Function
s = Rz(φ)

Spinor counter-clockwise rotation matrix with angle φ with respect to z-axis.

Arguments

  • φ: (::Real, [rad]) angle with respect to z-axis

Returns

  • s: (::Spinor) spinnor struct that represents the Rz rotation matrix
source

Plots

plot_phantom_map

KomaMRIPlots.plot_phantom_map — Function
p = plot_phantom_map(obj::Phantom, key::Symbol; kwargs...)

Plots a phantom map for a specific spin parameter given by key.

Arguments

  • obj: (::Phantom) Phantom struct
  • key: (::Symbol, opts: [:ρ, :T1, :T2, :T2s, :x, :y, :z]) symbol for displaying different parameters of the phantom spins

Keywords

  • t0: (::Real, =0, [ms]) time to see displacement of the phantom
  • height: (::Integer, =600) plot height
  • width: (::Integer, =nothing) plot width
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • view_2d: (::Bool, =false) boolean to indicate whether to use a 2D scatter plot
  • colorbar: (::Bool, =true) boolean to indicate whether to display a colorbar

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the phantom map for a specific spin parameter

References

Colormaps from https://github.com/markgriswold/MRFColormaps Towards Unified Colormaps for Quantitative MRF Data, Mark Griswold, et al. (2018).

Examples

julia> obj2D, obj3D = brain_phantom2D(), brain_phantom3D();
+\end{array}\right],\]
with $|\alpha|^2+|\beta|^2 = 1$.
This later operates on the $2\times2$ representation of $(x,y,z)$ as follows $V^{+} = R V R^{*}$.
Arguments
  • α: (::Complex{Float64}) Cayley-Klein parameter α
  • β: (::Complex{Float64}) Cayley-Klein parameter β
Returns
  • spinor: (::Spinor) Spinor struct
source

Q

KomaMRICore.Q — Function
s = Q(φ, nxy, nz)

Spinor rotation matrix. Counter-clockwise rotation of φ with respect to the axis of rotation n=(nx, ny, nz).

Pauly, J., Le Roux, P., Nishimura, D., & Macovski, A. (1991). Parameter relations for the Shinnar-Le Roux selective excitation pulse design algorithm (NMR imaging). IEEE Transactions on Medical Imaging, 10(1), 53-65. doi:10.1109/42.75611

\[\varphi=-\gamma\Delta t\sqrt{\left|B_{1}\right|^{2}+\left(\boldsymbol{G}\cdot\boldsymbol{x} +\right)^{2}}=-\gamma\Delta t\left\Vert \boldsymbol{B}\right\Vert\]

\[\boldsymbol{n}=\boldsymbol{B}/\left\Vert \boldsymbol{B}\right\Vert\]

Arguments

  • φ: (::Real, [rad]) φ angle
  • nxy: (::Real) nxy factor
  • nz: (::Real) nz factor

Returns

  • s: (::Spinor) spinnor struct that represents the Q rotation matrix
source

Un

KomaMRICore.Un — Function

Rodrigues' formula: Rotation matrix that when applied rotates with respect to "n" in an angle θ anti clock-wise

source

Rx

KomaMRICore.Rx — Function
s = Rx(θ)

Spinor counter-clockwise rotation matrix with angle θ with respect to x-axis.

Arguments

  • θ: (::Real, [rad]) angle with respect to x-axis

Returns

  • s: (::Spinor) spinor struct that represents the Rx rotation matrix
source

Ry

KomaMRICore.Ry — Function
s = Ry(θ)

Spinor counter-clockwise rotation matrix with angle θ with respect to y-axis.

Arguments

  • θ: (::Real, [rad]) angle with respect to y-axis

Returns

  • s: (::Spinor) spinor struct that represents the Ry rotation matrix
source

Rz

KomaMRICore.Rz — Function
s = Rz(φ)

Spinor counter-clockwise rotation matrix with angle φ with respect to z-axis.

Arguments

  • φ: (::Real, [rad]) angle with respect to z-axis

Returns

  • s: (::Spinor) spinnor struct that represents the Rz rotation matrix
source

Plots

plot_phantom_map

KomaMRIPlots.plot_phantom_map — Function
p = plot_phantom_map(obj::Phantom, key::Symbol; kwargs...)

Plots a phantom map for a specific spin parameter given by key.

Arguments

  • obj: (::Phantom) Phantom struct
  • key: (::Symbol, opts: [:ρ, :T1, :T2, :T2s, :x, :y, :z]) symbol for displaying different parameters of the phantom spins

Keywords

  • t0: (::Real, =0, [ms]) time to see displacement of the phantom
  • height: (::Integer, =600) plot height
  • width: (::Integer, =nothing) plot width
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • view_2d: (::Bool, =false) boolean to indicate whether to use a 2D scatter plot
  • colorbar: (::Bool, =true) boolean to indicate whether to display a colorbar

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the phantom map for a specific spin parameter

References

Colormaps from https://github.com/markgriswold/MRFColormaps Towards Unified Colormaps for Quantitative MRF Data, Mark Griswold, et al. (2018).

Examples

julia> obj2D, obj3D = brain_phantom2D(), brain_phantom3D();
 
 julia> plot_phantom_map(obj2D, :ρ)
 
-julia> plot_phantom_map(obj3D, :ρ)
source

plot_seq

KomaMRIPlots.plot_seq — Function
p = plot_seq(seq::Sequence; kwargs...)

Plots a sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title
  • freq_in_phase: (::Bool, =true) Include FM modulation in RF phase
  • gl: (::Bool, =false) use PlotlyJS.scattergl backend (faster)
  • max_rf_samples: (::Integer, =100) maximum number of RF samples
  • show_adc: (::Bool, =false) plot ADC samples with markers

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_phantom_map(obj3D, :ρ)
source

plot_seq

KomaMRIPlots.plot_seq — Function
p = plot_seq(seq::Sequence; kwargs...)

Plots a sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title
  • freq_in_phase: (::Bool, =true) Include FM modulation in RF phase
  • gl: (::Bool, =false) use PlotlyJS.scattergl backend (faster)
  • max_rf_samples: (::Integer, =100) maximum number of RF samples
  • show_adc: (::Bool, =false) plot ADC samples with markers

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_seq(seq)
source

plot_kspace

KomaMRIPlots.plot_kspace — Function
p = plot_kspace(seq::Sequence; width=nothing, height=nothing, darkmode=false)

Plots the k-space of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the k-space of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_seq(seq)
source

plot_kspace

KomaMRIPlots.plot_kspace — Function
p = plot_kspace(seq::Sequence; width=nothing, height=nothing, darkmode=false)

Plots the k-space of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the k-space of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_kspace(seq)
source

plot_M0

KomaMRIPlots.plot_M0 — Function
p = plot_M0(seq::Sequence; kwargs...)

Plots the zero order moment (M0) of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the moment M0 of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_kspace(seq)
source

plot_M0

KomaMRIPlots.plot_M0 — Function
p = plot_M0(seq::Sequence; kwargs...)

Plots the zero order moment (M0) of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the moment M0 of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_M0(seq)
source

plot_M1

KomaMRIPlots.plot_M1 — Function
p = plot_M1(seq::Sequence; kwargs...)

Plots the first order moment (M1) of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the moment M1 of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_M0(seq)
source

plot_M1

KomaMRIPlots.plot_M1 — Function
p = plot_M1(seq::Sequence; kwargs...)

Plots the first order moment (M1) of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the moment M1 of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_M1(seq)
source

plot_M2

KomaMRIPlots.plot_M2 — Function
p = plot_M2(seq::Sequence; kwargs...)

Plots the second order moment (M2) of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the moment M2 of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_M1(seq)
source

plot_M2

KomaMRIPlots.plot_M2 — Function
p = plot_M2(seq::Sequence; kwargs...)

Plots the second order moment (M2) of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the moment M2 of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_M2(seq)
source

plot_eddy_currents

KomaMRIPlots.plot_eddy_currents — Function
p = plot_eddy_currents(seq::Sequence, λ; kwargs...)

Plots the eddy currents of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct
  • λ: (::Real, [s]) time constant for the decay of Eddy currents

Keywords

  • α: (::Vector{Real}, =ones(size(λ))) eddy currents factors
  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the Eddy currents of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_M2(seq)
source

plot_eddy_currents

KomaMRIPlots.plot_eddy_currents — Function
p = plot_eddy_currents(seq::Sequence, λ; kwargs...)

Plots the eddy currents of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct
  • λ: (::Real, [s]) time constant for the decay of Eddy currents

Keywords

  • α: (::Vector{Real}, =ones(size(λ))) eddy currents factors
  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the Eddy currents of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_eddy_currents(seq, 80e-3)
source

plot_slew_rate

KomaMRIPlots.plot_slew_rate — Function
p = plot_slew_rate(seq::Sequence; kwargs...)

Plots the slew rate currents of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the slew rate currents of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_eddy_currents(seq, 80e-3)
source

plot_slew_rate

KomaMRIPlots.plot_slew_rate — Function
p = plot_slew_rate(seq::Sequence; kwargs...)

Plots the slew rate currents of a Sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the slew rate currents of the Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_slew_rate(seq)
source

plot_signal

KomaMRIPlots.plot_signal — Function
p = plot_signal(raw::RawAcquisitionData; kwargs...)

Plots a raw signal in ISMRMRD format.

Arguments

  • raw: (::RawAcquisitionData) RawAcquisitionData struct (raw signal in ISMRMRD format)

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the raw signal

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/3.koma_paper/comparison_accuracy/sequences/EPI/epi_100x100_TE100_FOV230.seq");
+julia> plot_slew_rate(seq)
source

plot_signal

KomaMRIPlots.plot_signal — Function
p = plot_signal(raw::RawAcquisitionData; kwargs...)

Plots a raw signal in ISMRMRD format.

Arguments

  • raw: (::RawAcquisitionData) RawAcquisitionData struct (raw signal in ISMRMRD format)

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • slider: (::Bool, =true) boolean to indicate whether to display a slider
  • show_seq_blocks: (::Bool, =false) boolean to indicate whether to display sequence blocks
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • range: (::Vector{Real}, =[]) time range to be displayed initially

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the raw signal

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/3.koma_paper/comparison_accuracy/sequences/EPI/epi_100x100_TE100_FOV230.seq");
 
 julia> sys, obj, seq = Scanner(), brain_phantom2D(), read_seq(seq_file)
 
 julia> raw = simulate(obj, seq, sys)
 
-julia> plot_signal(raw)
source

plot_image

KomaMRIPlots.plot_image — Function
p = plot_image(image; height, width, zmin, zmax, darkmode, title)

Plots an image matrix.

Arguments

  • image: (::Matrix{Number}) image matrix

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • zmin: (::Real, =minimum(abs.(image[:]))) reference value for minimum color
  • zmax: (::Real, =maximum(abs.(image[:]))) reference value for maximum color
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the image matrix
source

plot_dict

KomaMRIPlots.plot_dict — Function
str = plot_dict(dict::Dict)

Generates an HTML table based on the dictionary dict.

Arguments

  • dict: (::Dict) dictionary

Returns

  • str: (::String) dictionary as an HTML table
source

plot_seqd

KomaMRIPlots.plot_seqd — Function
p = plot_seqd(seq::Sequence; sampling_params=KomaMRIBase.default_sampling_params())

Plots a sampled sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • sampling_params: (::Dict{String,Any}(), =KomaMRIBase.default_sampling_params()) dictionary of sampling parameters

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the sampled Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
+julia> plot_signal(raw)
source

plot_image

KomaMRIPlots.plot_image — Function
p = plot_image(image; height, width, zmin, zmax, darkmode, title)

Plots an image matrix.

Arguments

  • image: (::Matrix{Number}) image matrix

Keywords

  • width: (::Integer, =nothing) plot width
  • height: (::Integer, =nothing) plot height
  • zmin: (::Real, =minimum(abs.(image[:]))) reference value for minimum color
  • zmax: (::Real, =maximum(abs.(image[:]))) reference value for maximum color
  • darkmode: (::Bool, =false) boolean to indicate whether to display darkmode style
  • title: (::String, ="") plot title

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the image matrix
source

plot_dict

KomaMRIPlots.plot_dict — Function
str = plot_dict(dict::Dict)

Generates an HTML table based on the dictionary dict.

Arguments

  • dict: (::Dict) dictionary

Returns

  • str: (::String) dictionary as an HTML table
source

plot_seqd

KomaMRIPlots.plot_seqd — Function
p = plot_seqd(seq::Sequence; sampling_params=KomaMRIBase.default_sampling_params())

Plots a sampled sequence struct.

Arguments

  • seq: (::Sequence) Sequence struct

Keywords

  • sampling_params: (::Dict{String,Any}(), =KomaMRIBase.default_sampling_params()) dictionary of sampling parameters

Returns

  • p: (::PlotlyJS.SyncPlot) plot of the sampled Sequence struct

Examples

julia> seq_file = joinpath(dirname(pathof(KomaMRI)), "../examples/1.sequences/spiral.seq")
 
 julia> seq = read_seq(seq_file)
 
-julia> plot_seqd(seq)
source

UI

KomaUI

KomaMRI.KomaUI — Function
out = KomaUI(; kwargs...)

Launch the Koma's UI.

Keywords

  • darkmode: (::Bool, =true) define dark mode style for the UI
  • frame: (::Bool, =true) display the upper frame of the Blink window
  • phantom_mode: (::String, ="2D", opts=["2D", "3D"]) load the default phantom as a 2D or 3D brain example
  • sim: (::Dict{String,Any}, =Dict{String,Any}()) simulation parameters dictionary
  • rec: (::Dict{Symbol,Any}, =Dict{Symbol,Any}()) reconstruction parameters dictionary
  • return_window: (::Bool, =false) make the out be either 'nothing' or the Blink window, depending on whether the return_window keyword argument is set to true
  • show_window: (::Bool, =true) display the Blink window

Returns

  • out: (::Nothing or ::Blink.AtomShell.Window) returns either 'nothing' or the Blink window, depending on whether the return_window keyword argument is set to true.

Examples

julia> KomaUI()
source
+julia> plot_seqd(seq)source

UI

KomaUI

KomaMRI.KomaUI — Function
out = KomaUI(; kwargs...)

Launch the Koma's UI.

Keywords

  • darkmode: (::Bool, =true) define dark mode style for the UI
  • frame: (::Bool, =true) display the upper frame of the Blink window
  • phantom_mode: (::String, ="2D", opts=["2D", "3D"]) load the default phantom as a 2D or 3D brain example
  • sim: (::Dict{String,Any}, =Dict{String,Any}()) simulation parameters dictionary
  • rec: (::Dict{Symbol,Any}, =Dict{Symbol,Any}()) reconstruction parameters dictionary
  • return_window: (::Bool, =false) make the out be either 'nothing' or the Blink window, depending on whether the return_window keyword argument is set to true
  • show_window: (::Bool, =true) display the Blink window

Returns

  • out: (::Nothing or ::Blink.AtomShell.Window) returns either 'nothing' or the Blink window, depending on whether the return_window keyword argument is set to true.

Examples

julia> KomaUI()
source
diff --git a/previews/PR284/assets/examples/1-seq.html b/previews/PR284/assets/examples/1-seq.html index 554aa4f03..e69eb23cc 100644 --- a/previews/PR284/assets/examples/1-seq.html +++ b/previews/PR284/assets/examples/1-seq.html @@ -9,7 +9,7 @@
@@ -17,9 +17,9 @@ window.PLOTLYENV = window.PLOTLYENV || {} - if (document.getElementById('27285551-629f-4696-a863-577b3292e434')) { + if (document.getElementById('24fe0e28-f317-41c1-b153-a62f0ffc633b')) { Plotly.newPlot( - '27285551-629f-4696-a863-577b3292e434', + '24fe0e28-f317-41c1-b153-a62f0ffc633b', [{"showlegend":true,"x":[null,null],"xaxis":"x","y":[null,null],"type":"scatter","name":"Gx","yaxis":"y","legendgroup":"Gx","hovertemplate":"(%{x:.4f} ms, %{y:.2f} mT/m)","marker":{"color":"#636EFA"}},{"showlegend":true,"x":[null,null],"xaxis":"x","y":[null,null],"type":"scatter","name":"Gy","yaxis":"y","legendgroup":"Gy","hovertemplate":"(%{x:.4f} ms, %{y:.2f} mT/m)","marker":{"color":"#EF553B"}},{"showlegend":true,"x":[null,null],"xaxis":"x","y":[null,null],"type":"scatter","name":"Gz","yaxis":"y","legendgroup":"Gz","hovertemplate":"(%{x:.4f} ms, %{y:.2f} 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deg SINC pulse (TBP=8, Hamming)"}, {"editable":false,"responsive":true,"staticPlot":false,"scrollZoom":true}, diff --git a/previews/PR284/create-your-own-phantom/index.html b/previews/PR284/create-your-own-phantom/index.html index 9623defbd..a6de37c0c 100644 --- a/previews/PR284/create-your-own-phantom/index.html +++ b/previews/PR284/create-your-own-phantom/index.html @@ -82,4 +82,4 @@ T2 = T2[ρ.!=0], T2s = T2s[ρ.!=0], Δw = Δw[ρ.!=0], -)

We can display the Phantom struct with the plot_phantom_map function. In this case we select the T1 decay to be displayed, but you can choose other property to be displayed:

plot_phantom_map(obj, :T1)
+)

We can display the Phantom struct with the plot_phantom_map function. In this case we select the T1 decay to be displayed, but you can choose other property to be displayed:

plot_phantom_map(obj, :T1)
diff --git a/previews/PR284/create-your-own-sequence/index.html b/previews/PR284/create-your-own-sequence/index.html index 81eb891d1..2bb403ab2 100644 --- a/previews/PR284/create-your-own-sequence/index.html +++ b/previews/PR284/create-your-own-sequence/index.html @@ -44,4 +44,4 @@ # Plot the sequence in time and its kspace plot_seq(seq; range=[0 30]) -plot_kspace(seq) +plot_kspace(seq) diff --git a/previews/PR284/educational-1d-simulation/index.html b/previews/PR284/educational-1d-simulation/index.html index fc090fc4a..760cb3e0d 100644 --- a/previews/PR284/educational-1d-simulation/index.html +++ b/previews/PR284/educational-1d-simulation/index.html @@ -2,4 +2,4 @@ Educational Material 📚 · KomaMRI.jl: General MRI simulation framework
GitHub
+ diff --git a/previews/PR284/events/index.html b/previews/PR284/events/index.html index 63a1c48a6..9a4d4b5f6 100644 --- a/previews/PR284/events/index.html +++ b/previews/PR284/events/index.html @@ -162,4 +162,4 @@ # Create two equivalent sequences in different ways sa = Sequence(R * [gx; gy; gz;;]) sb = R * Sequence([gx; gy; gz;;])
julia> all(sa.GR .≈ sb.GR)
-true
+true diff --git a/previews/PR284/generated/examples/01-FID/index.html b/previews/PR284/generated/examples/01-FID/index.html index 7ba5da2f7..ed66313c1 100644 --- a/previews/PR284/generated/examples/01-FID/index.html +++ b/previews/PR284/generated/examples/01-FID/index.html @@ -39,4 +39,4 @@

Finally, to simulate we will need to use the function simulate.

raw = simulate(obj, seq, sys)
RawAcquisitionData[SeqName: NoName | 1 Profile(s) of 8192×1]

To plot the results we will need to use the plot_signal function

p2 = plot_signal(raw; slider=false, height=300)
"../../assets/examples/1-signal.html"

Nice!, we can see that $S(t)$ follows an exponential decay $\exp(-t/T_2)$ as expected.

For a little bit of spiciness, let's add off-resonance to our example. We will use $\Delta f=-100\,\mathrm{Hz}$. For this, we will need to add a definition for Δw in our Phantom

obj = Phantom{Float64}(x=[0.], T1=[1000e-3], T2=[100e-3], Δw=[-2π*100])# and simulate again.
 
 raw = simulate(obj, seq, sys)
-p3 = plot_signal(raw; slider=false, height=300)
"../../assets/examples/1-signal2.html"

The signal now follows an exponential of the form $\exp(-t/T_2)\cdot\exp(-i\Delta\omega t)$. The addition of $\exp(-i\Delta\omega t)$ to the signal will generate a shift in the image space (Fourier shifting property). This effect will be better visualized and explained in later examples.

This page was generated using Literate.jl.

+p3 = plot_signal(raw; slider=false, height=300)
"../../assets/examples/1-signal2.html"

The signal now follows an exponential of the form $\exp(-t/T_2)\cdot\exp(-i\Delta\omega t)$. The addition of $\exp(-i\Delta\omega t)$ to the signal will generate a shift in the image space (Fourier shifting property). This effect will be better visualized and explained in later examples.

This page was generated using Literate.jl.

diff --git a/previews/PR284/generated/examples/02-SmallTipApproximation/index.html b/previews/PR284/generated/examples/02-SmallTipApproximation/index.html index 014416636..eb428dbdb 100644 --- a/previews/PR284/generated/examples/02-SmallTipApproximation/index.html +++ b/previews/PR284/generated/examples/02-SmallTipApproximation/index.html @@ -9,4 +9,4 @@ M = simulate_slice_profile(seq; z, sim_params)
"../../assets/examples/4b-profile.html"

This produces the following slice profile:

As you can see, for a flip angle of 30 deg, the slice profile is very close to the small tip angle approximation (the Fourier transform of $B_{1}(t)$).

But what will happen if we use a flip angle of 120 deg instead?

α_desired = 120 + 0im               # The multiplication of a complex number scales the RF pulse of a Sequence
 α = get_flip_angles(seq)[1] # Previous FA approx 30 deg
 seq = (α_desired / α) * seq         # Scaling the pulse to have a flip angle of 120
-M = simulate_slice_profile(seq; z, sim_params)
"../../assets/examples/4a-profile.html"

For this case, the small tip angle approximation breaks 😢, thus, the reason for its name!

This basic sinc pulse is not designed to be $B_{1}$-insensitive. Some adiabatic RF pulses have been proposed to achieve this. Watch out for a future example showing these adiabatic RF pulses 👀.

This page was generated using Literate.jl.

+M = simulate_slice_profile(seq; z, sim_params)
"../../assets/examples/4a-profile.html"

For this case, the small tip angle approximation breaks 😢, thus, the reason for its name!

This basic sinc pulse is not designed to be $B_{1}$-insensitive. Some adiabatic RF pulses have been proposed to achieve this. Watch out for a future example showing these adiabatic RF pulses 👀.

This page was generated using Literate.jl.

diff --git a/previews/PR284/generated/examples/03-ChemicalShiftEPI/index.html b/previews/PR284/generated/examples/03-ChemicalShiftEPI/index.html index c396d86e3..e7f5b2280 100644 --- a/previews/PR284/generated/examples/03-ChemicalShiftEPI/index.html +++ b/previews/PR284/generated/examples/03-ChemicalShiftEPI/index.html @@ -27,4 +27,4 @@ # Plotting the recon slice_abs = abs.(image[:, :, 1]) -p5 = plot_image(slice_abs; height=400)
"../../assets/examples/2-recon.html"

This page was generated using Literate.jl.

+p5 = plot_image(slice_abs; height=400)
"../../assets/examples/2-recon.html"

This page was generated using Literate.jl.

diff --git a/previews/PR284/generated/examples/04-3DSliceSelective/index.html b/previews/PR284/generated/examples/04-3DSliceSelective/index.html index b79418454..99d8d6fd3 100644 --- a/previews/PR284/generated/examples/04-3DSliceSelective/index.html +++ b/previews/PR284/generated/examples/04-3DSliceSelective/index.html @@ -31,4 +31,4 @@ # Plotting the slices p4 = plot_image(abs.(image[:, :, 1]); height=360, title="Slice 1") p5 = plot_image(abs.(image[:, :, 2]); height=360, title="Slice 2") -p6 = plot_image(abs.(image[:, :, 3]); height=360, title="Slice 3")
"../../assets/examples/3-recon3.html"

This page was generated using Literate.jl.

+p6 = plot_image(abs.(image[:, :, 3]); height=360, title="Slice 3")
"../../assets/examples/3-recon3.html"

This page was generated using Literate.jl.

diff --git a/previews/PR284/getting-started/index.html b/previews/PR284/getting-started/index.html index 74bd68a5f..494c719e7 100644 --- a/previews/PR284/getting-started/index.html +++ b/previews/PR284/getting-started/index.html @@ -3,4 +3,4 @@ (@v1.9) pkg> add KomaMRI

Then press Ctrl+C or backspace to return to the julia> prompt.

My First MRI Simulation

For our first simulation we will use KomaMRI's graphical user interface (GUI). For this, you will first need to load KomaMRI by typing using KomaMRI, and then launch the GUI with the KomaUI function.

julia> using KomaMRI
 
-julia> KomaUI()

The first time you use this command it may take more time than usual, but a window with the Koma GUI will pop up:

The user interface has some basic definitions for the scanner, phantom, and sequence already preloaded. So you can immediately interact with the simulation and reconstruction processes, and then visualize the results.

As a simple demonstration, press the Simulate! button and wait until the simulation is ready. Now you have acquired the Raw Signal and you should see the following:

Then, press the Reconstruct! button and wait until the reconstruction ends. Now you have reconstructed an Image from the Raw Signal and you should see the following in the GUI:

Congratulations, you successfully simulated an MRI acquisition! 🎊

+julia> KomaUI()

The first time you use this command it may take more time than usual, but a window with the Koma GUI will pop up:

The user interface has some basic definitions for the scanner, phantom, and sequence already preloaded. So you can immediately interact with the simulation and reconstruction processes, and then visualize the results.

As a simple demonstration, press the Simulate! button and wait until the simulation is ready. Now you have acquired the Raw Signal and you should see the following:

Then, press the Reconstruct! button and wait until the reconstruction ends. Now you have reconstructed an Image from the Raw Signal and you should see the following in the GUI:

Congratulations, you successfully simulated an MRI acquisition! 🎊

diff --git a/previews/PR284/index.html b/previews/PR284/index.html index c69382649..a194c1444 100644 --- a/previews/PR284/index.html +++ b/previews/PR284/index.html @@ -1,3 +1,3 @@ Home · KomaMRI.jl: General MRI simulation framework
GitHub

Introduction

KomaMRI is a Julia package meant to simulate general Magnetic Resonance Imaging (MRI) scenarios. Its name comes from the Japanese word for spinning-top こま (ko-ma) as they precess due to gravity like spins in a magnetic field.

KomaMRI generates raw data by solving the Bloch equations using the specified scanner, phantom and sequence. It also provides a Graphical User Interface (GUI) that encapsulates the whole imaging pipeline (simulation and reconstruction).

-

KomaMRI can be used in different environments:

  • User Interface: User-friendly interaction. No Julia programming skills are required. Refer to the User Interface Section to dive into the details of how to use the GUI.

  • Scripts : Basic knowledge of Julia is required. Refer to the Scripts Section to follow a basic workflow on how to work with KomaMRI.

  • Notebooks: Basic knowledge of Julia is required. This serves as an alternative development environment featuring user-friendly interactive tools. For guidance on setting up these environments, refer to the Notebooks Section.

If you are new to KomaMRI, we recommend starting with the Getting Started Section to install Julia, KomaMRI, and perform your first simulation.

Features

Some of the features of KomaMRI are:

  • Fast simulations by using CPU and GPU parallelization 🏃💨.
  • Open Source, so anyone can include additional features 🆙.
  • Compatibility with community-standards 🤝 like Pulseq .seq and ISMRMRD .mrd.
  • Compatibility with Pluto and Jupyter notebooks 🎈
  • Cross-platform 🌐 thanks to the use of the Julia programming language.
  • Friendly user interface for people with no programming skills 😌.
  • Flexible API for advanced users 👨‍💻.

Potential Use Cases

We see Koma being used in:

  • The generation of synthetic data to train Machine Learning models.
  • To test novel pulse sequences before implementing them directly in a real scanner (with a Pulseq sequence).
  • Teaching exercises for MRI acquisition or reconstruction.
+

KomaMRI can be used in different environments:

If you are new to KomaMRI, we recommend starting with the Getting Started Section to install Julia, KomaMRI, and perform your first simulation.

Features

Some of the features of KomaMRI are:

Potential Use Cases

We see Koma being used in:

diff --git a/previews/PR284/mri-theory-informal/index.html b/previews/PR284/mri-theory-informal/index.html index d72dd4e45..e33f2dc26 100644 --- a/previews/PR284/mri-theory-informal/index.html +++ b/previews/PR284/mri-theory-informal/index.html @@ -120,4 +120,4 @@ \end{pmatrix} = \int_{x} \int_{y} \int_{z} \vec{M}(x, y, z, t) -\: \mathrm{d}z \: \mathrm{d}y \: \mathrm{d}x\]

+\: \mathrm{d}z \: \mathrm{d}y \: \mathrm{d}x\]

diff --git a/previews/PR284/mri-theory/index.html b/previews/PR284/mri-theory/index.html index 5cbcd7a29..8e8b89e7e 100644 --- a/previews/PR284/mri-theory/index.html +++ b/previews/PR284/mri-theory/index.html @@ -84,4 +84,4 @@ # Define the plots for traverse and longitudinal magnetizations pxy = plot(abs.(sig[:,:,1])); -pz = plot(abs.(sig[:,:,2]));
julia> [pxy pz]
+pz = plot(abs.(sig[:,:,2]));
julia> [pxy pz]
diff --git a/previews/PR284/notebooks/index.html b/previews/PR284/notebooks/index.html index 2158891eb..cda3a4628 100644 --- a/previews/PR284/notebooks/index.html +++ b/previews/PR284/notebooks/index.html @@ -25,4 +25,4 @@ seq += acq # adding ADC-only block # Plot the sequence -plot_seq(seq; slider=false, height=300)

This should be sufficient, and now you can start working with KomaMRI using Jupyter notebooks.

If you encounter the issue of WebIO not being detected:

Refer to this IJulia documentation and this troubleshooting guide for details. Essentially, you need to install a WebIO extension depending on your Jupyter installation.

+plot_seq(seq; slider=false, height=300)

This should be sufficient, and now you can start working with KomaMRI using Jupyter notebooks.

If you encounter the issue of WebIO not being detected:

Refer to this IJulia documentation and this troubleshooting guide for details. Essentially, you need to install a WebIO extension depending on your Jupyter installation.

diff --git a/previews/PR284/programming-workflow/index.html b/previews/PR284/programming-workflow/index.html index 1af2ec00f..fffc77227 100644 --- a/previews/PR284/programming-workflow/index.html +++ b/previews/PR284/programming-workflow/index.html @@ -106,4 +106,4 @@ raw = simulate(obj, seq, sys; sim_params) # Save the .mat file in the temp directory -matwrite(joinpath(tempdir(), "koma-raw.mat"), Dict("raw" => raw))

Note that we need to simulate to return an array type (not the default RawAcquisitionData), and then we utilize the matwrite function to save a file named "koma-raw.mat" in your computer's temporary directory. Now, you can navigate to your temporary directory (which you can find by displaying the result of tempdir() in the Julia REPL) and locate the "koma-raw.mat" file.

+matwrite(joinpath(tempdir(), "koma-raw.mat"), Dict("raw" => raw))

Note that we need to simulate to return an array type (not the default RawAcquisitionData), and then we utilize the matwrite function to save a file named "koma-raw.mat" in your computer's temporary directory. Now, you can navigate to your temporary directory (which you can find by displaying the result of tempdir() in the Julia REPL) and locate the "koma-raw.mat" file.

diff --git a/previews/PR284/sequence/index.html b/previews/PR284/sequence/index.html index d98429b11..8e7fda837 100644 --- a/previews/PR284/sequence/index.html +++ b/previews/PR284/sequence/index.html @@ -55,4 +55,4 @@ julia> seq = s + s + s Sequence[ τ = 11.512 ms | blocks: 33 | ADC: 15 | GR: 33 | RF: 3 | DEF: 5 ] -julia> plot_seq(seq; slider=false) +julia> plot_seq(seq; slider=false) diff --git a/previews/PR284/ui-details/index.html b/previews/PR284/ui-details/index.html index 3df126643..cb9f3952d 100644 --- a/previews/PR284/ui-details/index.html +++ b/previews/PR284/ui-details/index.html @@ -1,4 +1,4 @@ User Interface · KomaMRI.jl: General MRI simulation framework
GitHub

User Interface

This section provides a comprehensive guide on using the User Interface of the KomaMRI package and delves into the internal processes that occur during interaction. By the end of this section, you will be equipped to execute a complete workflow even without any prior programming experience.

Basic Workflow

(You can also go to analog steps using Scripts)

As a general overview, remember the following workflow steps when using KomaMRI:

  • Loading Simulation Inputs: Scanner, Phantom, Sequence
  • Running Simulation
  • Reconstructing Image using MRIReco

In the following subsections, we will cover all the mentioned steps. First, open the Julia REPL and enter the following commands to include the KomaMRI package and launch the user interface:

julia> using KomaMRI
 
-julia> KomaUI()

Loading Simulation Inputs

(You can also go to analog steps using Scripts)

The user interface has preloaded certain inputs into RAM, including the Scanner, Phantom, and Sequence structs. In the following subsections, we will demonstrate how to visualize these inputs.

Scanner

You can visualize the preloaded Scanner struct by clicking on the Scanner dropdown and then pressing the View Scanner button. The Scanner struct contains hardware-related information, such as the main magnetic field's magnitude:

Phantom

To see the phantom already stored in RAM, simply click on the Phantom dropdown an then press the View Phantom button. The preloaded phantom is a slice of a brain:

It is also possible to load .h5 phantom files. The KomaMRI.jl has some examples stored at ~/.julia/packages/KomaMRI/<id-string>/examples/2.phantoms/. For instance, let's load the sphere_chemical_shift.h5 file:

Note that you can select different spin parameters to visualize like ρ, T1, T2, among others.

Sequence

There are two options to visualize the sequence already preloaded in RAM: in the time domain or in the k-space. The preloaded sequence is a single-shot EPI.

For visualization of the sequence in the time domain, click on the Sequence dropdown and then press the Sequence (MPS) button:

For visualization of the sequence in the k-space, click on the Sequence dropdown and then press the k-space button:

You can also display the Moments related to the Sequence by pressing the View Moments and then pressing the buttons for zero, first and second moments.

It is also possible to load Pulseq compatible .seq sequence files. The KomaMRI has some examples stored at ~/.julia/packages/KomaMRI/<id-string>/examples/1.sequences/. For instance, let's load the spiral.seq file and view it the time domain and k-space:

And remember, you are free to interact with the plots:

Running Simulation

(You can also go to analog steps using Scripts)

Once the inputs are loaded in RAM, it is possible to perform the simulation to get the Raw Signal.

Simulation Parameters

To visualize the default simulation parameters, click on the Simulate! dropdown and then press the View Options button:

Visualization of the Raw Signal

Press the Simulate! button to perform the simulation (this may take a while). Automatically the generated Raw Signal should be displayed or you can click on the Raw Data dropdown and then press the View Raw Data button:

Reconstructing Image using MRIReco

(You can also go to analog steps using Scripts)

Once the Raw Signal is loaded in RAM, it is possible to reconstruct the image.

Reconstruction Parameters

To visualize the default reconstruction parameters, click on the Reconstruct! dropdown and then press the View Options button:

Visualization of the Image

Press the Reconstruct! button to perform the reconstruction (this may take a while). Automatically the generated Image should be displayed or you can click on the he Reconstruct! dropdown and then press the |Image| button:

Exporting Results to .mat File

(You can also go to analog steps using Scripts)

The user interface has the option to save the results in .mat format. Simply click on the Export to .mat and you have the alternatives to get data independently or you can press the All button to have all the results given by the simulator:

So far, and due to limitations of the user interface dependencies, the .mat files are saved in the temporal directory of your computer OS, which can be found by typing the tempdir() command in the Julia REPL:

REPL and UI communication

An amazing feature of KomaMRI is that it allows you to modify certain variables in the Julia REPL, and then the user interface automatically updates its plots in real-time:

The variables that update the interface are:

  • seq_ui[] for the Sequence
  • obj_ui[] for the Phantom
  • sys_ui[] for the Scanner
  • raw_ui[] for the Raw Signal
  • img_ui[] for the Image

Don't forget to add the brackets [] to these variables, otherwise it won't work.

+julia> KomaUI()

Loading Simulation Inputs

(You can also go to analog steps using Scripts)

The user interface has preloaded certain inputs into RAM, including the Scanner, Phantom, and Sequence structs. In the following subsections, we will demonstrate how to visualize these inputs.

Scanner

You can visualize the preloaded Scanner struct by clicking on the Scanner dropdown and then pressing the View Scanner button. The Scanner struct contains hardware-related information, such as the main magnetic field's magnitude:

Phantom

To see the phantom already stored in RAM, simply click on the Phantom dropdown an then press the View Phantom button. The preloaded phantom is a slice of a brain:

It is also possible to load .h5 phantom files. The KomaMRI.jl has some examples stored at ~/.julia/packages/KomaMRI/<id-string>/examples/2.phantoms/. For instance, let's load the sphere_chemical_shift.h5 file:

Note that you can select different spin parameters to visualize like ρ, T1, T2, among others.

Sequence

There are two options to visualize the sequence already preloaded in RAM: in the time domain or in the k-space. The preloaded sequence is a single-shot EPI.

For visualization of the sequence in the time domain, click on the Sequence dropdown and then press the Sequence (MPS) button:

For visualization of the sequence in the k-space, click on the Sequence dropdown and then press the k-space button:

You can also display the Moments related to the Sequence by pressing the View Moments and then pressing the buttons for zero, first and second moments.

It is also possible to load Pulseq compatible .seq sequence files. The KomaMRI has some examples stored at ~/.julia/packages/KomaMRI/<id-string>/examples/1.sequences/. For instance, let's load the spiral.seq file and view it the time domain and k-space:

And remember, you are free to interact with the plots:

Running Simulation

(You can also go to analog steps using Scripts)

Once the inputs are loaded in RAM, it is possible to perform the simulation to get the Raw Signal.

Simulation Parameters

To visualize the default simulation parameters, click on the Simulate! dropdown and then press the View Options button:

Visualization of the Raw Signal

Press the Simulate! button to perform the simulation (this may take a while). Automatically the generated Raw Signal should be displayed or you can click on the Raw Data dropdown and then press the View Raw Data button:

Reconstructing Image using MRIReco

(You can also go to analog steps using Scripts)

Once the Raw Signal is loaded in RAM, it is possible to reconstruct the image.

Reconstruction Parameters

To visualize the default reconstruction parameters, click on the Reconstruct! dropdown and then press the View Options button:

Visualization of the Image

Press the Reconstruct! button to perform the reconstruction (this may take a while). Automatically the generated Image should be displayed or you can click on the he Reconstruct! dropdown and then press the |Image| button:

Exporting Results to .mat File

(You can also go to analog steps using Scripts)

The user interface has the option to save the results in .mat format. Simply click on the Export to .mat and you have the alternatives to get data independently or you can press the All button to have all the results given by the simulator:

So far, and due to limitations of the user interface dependencies, the .mat files are saved in the temporal directory of your computer OS, which can be found by typing the tempdir() command in the Julia REPL:

REPL and UI communication

An amazing feature of KomaMRI is that it allows you to modify certain variables in the Julia REPL, and then the user interface automatically updates its plots in real-time:

The variables that update the interface are:

Don't forget to add the brackets [] to these variables, otherwise it won't work.

diff --git a/previews/PR284/ways-of-using-koma/index.html b/previews/PR284/ways-of-using-koma/index.html index 4252e1bec..ea8122905 100644 --- a/previews/PR284/ways-of-using-koma/index.html +++ b/previews/PR284/ways-of-using-koma/index.html @@ -134,4 +134,4 @@ seq += acq # adding ADC-only block # Plot the sequence -plot_seq(seq; slider=false, height=300)

This should be sufficient, and now you can start working with KomaMRI using Jupyter notebooks.

If you encounter the issue of WebIO not being detected:

Refer to this troubleshooting guide for details. Essentially, you need to install a WebIO extension based on your Jupyter installation.

+plot_seq(seq; slider=false, height=300)

This should be sufficient, and now you can start working with KomaMRI using Jupyter notebooks.

If you encounter the issue of WebIO not being detected:

Refer to this troubleshooting guide for details. Essentially, you need to install a WebIO extension based on your Jupyter installation.