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SETUP.md

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MRM Sengupta CMT Golden Angle

Requirements:

  • Python - for image reconstruction
  • MATLAB - for figure creation

Tested Configuration:

  • Mac OS X 10.7.5 (Lion)
  • Python 2.7.8 Anaconda 2.0.1 (x86_64)
  • MATLAB R0210a

Installation Options:

  • Click the Download ZIP button on the lower right hand side of the repository to download the code to your local machine
  • OR clone the git repository to your local machine
  • OR fork to your own GitHub repository and then clone the git repository to your local machine

Usage Steps:

  • Run ./code/download_data_all.py to download the raw CMT k-space data files in MATLAB .mat V5 format to the ../data_input/ folder. Downloaded files come packaged in .zip files that are automatically extracted. MD5 checksums are verified for all downloaded files.

  • Run ./code/CMT_Recon.py to generate 32 reconstructions (about 1 GB each). Output data files are written to the ./data_output/ folder.

  • Run ./code/CMT_Figure_*.m to reproduce figures from the paper. Figures are written in .tif format in the ./figures/ folder. All figures can be created by executing ./code/CMT_Figures_Create_All.m.

Example:

  • Raw Data File : Human_LA_256p.mat : Linear Angle data acquired with 256 profiles per 180 degrees.

  • Reconstructed Data File : Human_LA_256p_203.mat : Above data set reconstructed with 203 profiles per slice.

  • Figure File : Figure_2A_2B.tif : Figure_2A_2B reproduced from above (and other) reconstructed image volumes.

Notes:

  • The scripts ./code/download_data_verify_all.py and ./code/download_data_verify_all.m verify the MD5 hash values for all ./data_input/ files.
  • Files in ./data_input/, ./data_output/, and ./figures/ (other than README.md) are ignored when performing git commit.