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Jayvik_fMRI

  • Preprocessing Pipeline
    • AFNI
      • nifti_to_afni_conversion.txt: command line codes to convert between BRIK/HEAD and NIFTI files
      • template_afni_proc.py: afni's default pre-processing pipeline template structure, would probably work well with human brains
    • Mask_maker
      • model_2d_contrast_full_2.h5: deep learning model to generate masks for mice structural images
      • T1_RARE_mask_maker.py: code to run the masking model
      • binarizer.py: erode and dilate mask to clean it up
    • pipeline.py: full pre-processing pipeline from start to finish ***
    • random
      • collect_filenames.py: collects all filenames in a folder
      • graymatter.py: generates gray matter mask from csf, wm, and atlas masks
      • restack_slices.py: takes fMRI 3D Volumes and restacks into 4D NIFTI
      • separate_slices.py: takes fMRI 4D NIFTI and breaks down into 3D volumes
      • T1_resampler.py: resamples T1 images to 0.3mm^3 resolution
  • Analysis
    • melodic.py: code to run FSL Melodic from terminal (important for mice since it can bypass masking step)
    • gift_setup.py: sets up files and filenames for Group ICA of fMRI Toolbox to organize better (important because subjects need to be in their own folder)
    • conn_setup.py: sets up files and filenames for Conn Toolbox (*** INCOMPLETE ***)
    • batch_test.m: sets up conn to run. Run file in matlab, type conn_batch(BATCH) in matlab terminal, open conn and open project
  • NyquistGhost: document containing nyquist ghost research, papers, links to githubs of codes. (Minnesota code is of interest)
  • Archive: unnecessary or incomplete scripts
    • conn_setup.py: sets up files and filenames for Conn Toolbox (*** INCOMPLETE ***)
    • apply_mask.py: applies mask by multiplication between 2 nifti files (*** already part of pipeline.py ***)
    • echo_extracting.py: extracts the first of 3 echos of a 4D image and removes the first 4 of those echos (*** already part of pipeline.py ***)
    • register_volumes_and_combine.py: registers volumes using ANTs (*** already part of pipeline.py ***)

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