Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Introduce new models #39

Open
Lestropie opened this issue Dec 1, 2021 · 1 comment
Open

Introduce new models #39

Lestropie opened this issue Dec 1, 2021 · 1 comment

Comments

@Lestropie
Copy link
Collaborator

There will always be new diffusion models that could be introduced into the specification. The intention is for the framework of the specification to be sufficiently general and extensible to be possible to utilise directly for new models, though precedents such as filename suffix & model parameter dictionary can still be set by introducing that model into the specification.

This issue is intended to serve as a list of prospective models that could be introduced into the specification, and to link to relevant Issues / PRs as necessary. The Issue will additionally be used to stash content from models that have been removed from earlier drafts of the specification.

For each model, we ideally don't want to base the specification off of one specific software implementation; the proposal needs to be compatible with all softwares providing implementations of that model. So proposal for inclusion of any of these models will need to include a search and listing of all relevant softwares.


  • [] Constant Solid Angle (CSA)
    Manuscript

  • [] Diffusion Kurtosis Imaging (DKI)
    Manuscript

  • [] Diffusion Spectrum Imaging (DSI)
    Manuscript

  • [] Fiber ORientation Estimated using Continuous Axially Symmetric Tensors (FORECAST)
    Manuscript

  • [] Free water DTI
    (Unsure whether this should be a "separate model", or whether it should be an integral part of the DTI model, with some instances simply failing to estimate the free water component)

  • [] Mean Apparent Propagator MRI
    Manuscript

  • [] NODDI
    Manuscript

  • [] Q-Ball Imaging (QBI)
    Original manuscript
    SH version

  • [] SHORE

  • [] White Matter Tract Integrity (WMTI)
    Manuscript

@Lestropie
Copy link
Collaborator Author

Lestropie commented Dec 1, 2021

Old draft contents for models removed in #40

Intrinsic model parameters

Model label Full Name Data representation
csa Constant Solid Angle [Aganj2010] Spherical harmonics image
dki Diffusion Kurtosis Imaging [Jensen2005] Single parameter vectors image with parameter name "all" with 21 volumes in the order: Dxx, Dxy, Dxz, Dyy, Dyz, Dzz, Wxxxx, Wyyyy, Wzzzz, Wxxxy, Wxxxz, Wxyyy, Wyyyz, Wxzzz, Wyzzz, Wxxyy, Wxxzz, Wyyzz, Wxxyz, Wxyyz, Wxyzz (D is the diffusion tensor, W is the kurtosis tensor)
OR
6 diffusion tensor coefficients as parameter vectors image with parameter name "tensor";
15 kurtosis tensor coefficients as parameter vectors image with parameter name "kurtosis";
Optional: estimated b=0 intensity as scalar image with parameter name "bzero"
dsi Diffusion Spectrum Imaging [Wedeen2008],[Paquette2017] Probability distribution functions
forecast Fiber ORientation Estimated using Continuous Axially Symmetric Tensors [Zuchelli2017] Spherical harmonics image
fwdti Free water DTI [Hoy2015] One parameter vectors image with parameter name "tensor", containing 6 volumes in the order: Dcxx, Dcxy, Dcxz, Dcyy, Dcyz, Dczz (Dc is the free-water-corrected diffusion tensor);
One scalar image with parameter name "fwf" corresponding to the estimated free water fraction
mapmri Mean Apparent Propagator MRI [Ozarslan2013]
noddi Neurite Orientation Dispersion and Density Imaging [Zhang2012],[Daducci2015] Three scalar images, with parameter names equal to {"icvf", "isovf", "od"} (ICVF is the “intracellular volume fraction” (also known as NDI); ISOVF is the "isotropic component volume fraction"; OD is the “orientation dispersion” (the variance of the Watson distribution; also known as ODI));
One 3-vectors image with parameter name "direction" to provide the estimated fibre orientation
qbi Q-Ball Imaging [Tuch2004], [Hess2006] Single amplitudes image
OR
Single spherical harmonics image
shore Simple Harmonic Oscillator-based Re[construction and Estimation [Ozarslan2008]
wmti White Matter Tract Integrity [Fieremans2011] One parameter vectors image with parameter name "coeffs", with 33 volumes in the order: Dxx, Dxy, Dxz, Dyy, Dyz, Dzz, Wxxxx, Wyyyy, Wzzzz, Wxxxy, Wxxxz, Wxyyy, Wyyyz, Wxzzz, Wyzzz, Wxxyy, Wxxzz, Wyyzz, Wxxyz, Wxyyz, Wxyzz, Dhxx, Dhxy, Dhxz, Dhyy, Dhyz, Dhzz, Drxx, Drxy, Drxz, Dryy, Dryz, Drzz (D is the diffusion tensor and W is the kurtosis tensor);
One scalar image with parameter name "awf", representing the estimated axonal water fraction

Input model parameters

  • csa :

    • SphericalHarmonicOrder : value
    • Smoothing : value
    • Basis : value
  • dsi :

    • GridSize : value
    • RStart : value
    • RStep : value
    • REnd : value
    • FilterWidth : value
  • forecast :

    • Sphere : value
    • DecAlg : value
    • LambdaLb : value
    • SphericalHarmonicsOrder : value
  • mapmri :

    • RadialOrder : value
    • LaplacianRegularization : bool
    • LaplacianWeighting : value
    • PositivityConstraint : bool
    • Tau : value
    • ConstrainE0 : value
    • PositiveConstraint : value
    • PosGrid : value
    • PosRadius : value
    • AnisotropicScaling : bool
    • EigenvalueThreshold : value
    • PosGrid : value
    • BvalThreshold : value
    • DTIScaleEstimation : bool
    • StaticDiffusivity : value
  • noddi:

    • DPar : value
    • DIso : value
    • Lambda1 : value
    • Lambda2 : value
  • shore :

    • RadialOrder : value
    • Zeta : value
    • LambdaN : value
    • LambdaL : value
    • Tau : value
    • ConstrainE0 : value
    • PositiveConstraint : value
    • PosGrid : value
    • PosRadius : value

Extrinsic model parameters

<parameter> value Description Data representation Possible Model sources Unit or scale
ak Axial kurtosis Scalar { dki, wmti } Unitless
mk Mean kurtosis Scalar { dki, wmti } Unitless
msd Mean-Squared Displacement Scalar { mapmri, shore }
pdf Diffusion propagator 3-vectors
rk Radial kurtosis Scalar { dki, wmti } Unitless
rtap Return To Axis Probability Scalar { mapmri } Probability [0.0-1.0]
rtop Return To Origin Probability Scalar { shore } Probability [0.0-1.0]
rtpp Return To Plane Probability Scalar { mapmri } Probability [0.0-1.0]
tort Tortuosity of extra-cellular space Scalar { dki }

Demonstrative examples

  • A NODDI fit:

    my_diffusion_pipeline/
        sub-01/
            dwi/
                sub-01_parameter-icvf_noddi.nii.gz
                sub-01_parameter-isovf_noddi.nii.gz
                sub-01_parameter-od_noddi.nii.gz
                sub-01_parameter-direction_noddi.nii.gz
                sub-01_parameter-direction_noddi.json
                sub-01_noddi.json
    

    Dimensions of NIfTI image "sub-01_parameter-icvf_noddi.nii.gz": IxJxK (scalar)
    Dimensions of NIfTI image "sub-01_parameter-isovf_noddi.nii.gz": IxJxK (scalar)
    Dimensions of NIfTI image "sub-01_parameter-od_noddi.nii.gz": IxJxK (scalar)
    Dimensions of NIfTI image "sub-01_parameter-direction_noddi.nii.gz": IxJxKx3 (3-vectors)

    Contents of file "sub-01_noddi.json" (common to all intrinsic model parameter images):

    {
        "Model": "Neurite Orientation Dispersion and Density Imaging (NODDI)",
        "ModelURL": "https://www.nitrc.org/projects/noddi_toolbox"
    }

    Contents of JSON file "sub-01_parameter-direction_noddi.json":

    {
        "OrientationRepresentation": "3vector",
        "ReferenceAxes": "???"
    }

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant