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RRSG/qMRSG 2020 ISMRM Challenge - T1 mapping processing pipeline

Processed T1 maps

The processed T1 maps have been uploaded in the RRSG/qMRSG 2020 ISMRM Challenge OSF.io repository, under the folder challenge_t1_maps. The folders are organised in the same structure as the challenge_submissions folder, which contain the raw data. Each T1 map zip file contains 1) T1 maps, 2) YAML/JSON configuration files that contain the challenge submissions details, 3) T1 maps saved as PNG images for quality assurance purposes, and 4) a text file with the link to the raw data used to fit the accompanying T1 map.

Running this pipeline with CodeOcean

Coming soon.

Environment setup instructions to run notebook

These instructions were tested on a Macbook, and will likely be identical for Linux. The syntax for Windows might be different, depending on the shell you're using to install the Python packages. The shell that comes with Anaconda would likely work well.

  • Clone or download this GitHub repository

(Recommended) Create a conda virtual environment.

  • conda create -n sos_matlab python=3.6
  • conda activate sos_matlab
  • conda install ipython=7.2.0

Setup the MATLAB Engine API for Python

  • cd /Applications/MATLAB_R2018b.app/extern/engines/python/
    • Replace MATLAB_R2018b.app with whatever version of MATLAB you have.
  • python setup.py install

Install neessary Python packages

  • pip install sos==0.21.6 sos-bash==0.12.3 sos-javascript==0.9.12.2 sos-julia==0.9.12.1 sos-matlab==0.18.4 sos-notebook==0.21.9 sos-python==0.9.12.1 sos-r==0.9.12.2 sos-ruby==0.9.15.0 sos-sas==0.9.12.3 scipy numpy imatlab;

Install the MATLAB and SOS Jupyter kernels

  • python -mimatlab install
  • python -m sos_notebook.install

Start a Jupyter session

  • jupyter notebook RRSG_T1_fitting.ipynb
  • Choose the configuration file you want to use in the first cell
  • Run all cells

GIFs of T1 maps for datasets

3T - Human

3T - NIST

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Pipeline to fit all the inversion recovery datasets

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