https://github.com/kerkelae/scnn-investigation

Code for reproducing the results of my spherical CNN paper.
https://github.com/kerkelae/scnn-investigation

Last synced: about 9 hours ago
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Code for reproducing the results of my spherical CNN paper.

• Host: GitHub
• URL: https://github.com/kerkelae/scnn-investigation
• Owner: kerkelae
• License: mit
• Created: 2023-09-21T10:31:25.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-10-16T09:18:22.000Z (4 months ago)
• Last Synced: 2024-10-18T00:47:38.408Z (4 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
# sCNN Investigation

This repository contains the code (not data) for the following paper:

- Kerkelä L, Seunarine K, Szczepankiewicz F and Clark CA (2024) _Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data._ Front. Neuroimaging 3:1349415. doi: [10.3389/fnimg.2024.1349415](https://doi.org/10.3389/fnimg.2024.1349415)

The sCNN implementation can be found in the `scnn` package. I used the Conda environment `environment/scnn.yml` to run the code except that `environment/dmipy.yml` was used for conventional fitting.