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ImageProcessing

Using Python

Installation Guide:

Python 3.9 and above

Libarary: numpy, roifile, matplotlib, opencv, pandas, scipy, scikit-learn, scikit-image, joblib (parallel computing), PyImageJ (which also requires OpenJDK 11 and Maven) https://py.imagej.net/en/latest/Install.html

Use either "conda install numpy" or "pip install pyimagej" in the Anaconda terminal

Download and install fiji.app https://imagej.net/software/fiji/ Make sure the newest fiji contains: “…\plugins\Descriptor_based_registration-2.1.8.jar” in the "plugins" folder

ClusterSeqIP_v2.py

Pre-process the raw images from the Seq run and output processed images in a folder that is ready for color transformation

What it does:

Image rename, filtering, binning, background normalization, magnification correction, image registration and cropping, illumination correction

Executing Program:

Before running it, first make sure Fiji.app is downloaded and installed PyImageJ, OpenJDK 11 and Maven are all properly installed Then open the script and make sure JAVA_HOME is set to the correct directory in your PC os.environ['JAVA_HOME']='C:\Program Files\Microsoft\jdk-11.0.21.9-hotspot' and same for the fiji parth fijipath='...your directory/Fiji.app'

Last, run the file in the terminal with "-i +your_raw_image_folder"

& C:/Users/...your directory/python.exe "...your directory/ClusterSeqIP_v2.py" -i "/your_path_to/raw_image_folder"

Python will call fiji algorithm to perform the image registration, requires users to drag the cropping rectangle to center and manually adjust the threshold to ~0.08

Input:

Raw .tif image folder path (don't put things that are not .tif files in that folder)

Output:

2_preprocess: this folder stores preprocessed images (for debugging, and manual registration) 2_Regis: this folder stores the registered images for enduse to visualize and check the registration quality 2_processed_final: this folder stores the final processed images for next step color transformation, pass this directory to the color_transform.py once you believe all the images are properly processed and would like to move on.

Using MATLAB

ClusterSeqIP_v2_IJauto.m is the matlab version of the ClusterSeqIP_v2.py that will complete the entire image processing pipeline:

Installation Guide:

MATLAB R2020 and above

Download and install fiji.app https://imagej.net/software/fiji/ MATLAB imageJ: mij.jar, ij.jar Make sure the fiji contains: “…\plugins\Descriptor_based_registration-2.1.8.jar”

Executing program:

First, Add mij.jar, ij.jar and Descriptor_based_registration-2.1.8.jar to the script path

ImgFolderPath='Your Raw Image Path Folder'; %Replace this with the folder path of your raw images

Click “Run” button, the processed images will be output in the same directory of your raw image path.

Legal

The attached LICENSE.md solely authorizes the use of the software contained in this repository and provides no other license.

Usage of Lightning Terminators™️ is governed by a separate license provided upon purchase.

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Seq raw Image processing and auto-ROI in Python

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