Skip to content

Latest commit

 

History

History
34 lines (31 loc) · 1.38 KB

README.md

File metadata and controls

34 lines (31 loc) · 1.38 KB

Data

Data availability

We plan to host the dataset on a publicly accessible server and make it available upon request. In the meantime, please contact Dr. Maria del C. Valdés-Hernández ([email protected]) to inquire about the dataset used in this work.

Data folder structure

  • Data should have the following structure
    clinical-super-mri/
        data/
            affine/
                SR_002_NHSRI_V0_affine.mat
                SR_002_NHSRI_V1_affine.mat
                SR_005_BRIC1_V0_affine.mat
                ...
            rigid/
                SR_002_NHSRI_V0_rigid.mat
                SR_002_NHSRI_V1_rigid.mat
                SR_005_BRIC1_V0_rigid.mat
                ...
            warp/
                SR_002_NHSRI_V0.mat
                SR_002_NHSRI_V1.mat
                SR_005_BRIC1_V0.mat
                ...
    

Convert .mat to .npy

  • Here we provide a simple Python script mat2npy.py to convert .mat files to .npy as loading .npy files is much faster in Python.
  • The follow command convert all .mat scans in affine/ to .npy files and store in affine/npy
    python mat2npy.py --input_dir affine --output_dir affine/npy
    
  • Note that our data reader still support reading directly from .mat files though the training speed might be bottlenecked by reading .mat files.