/BundleCleaner

Unsupervised Denoising and Subsampling of Diffusion MRI-Derived Tractography Data

Primary LanguagePython

BundleCleaner: Unsupervised Denoising and Subsampling of Tractography Data

Author: Yixue Feng

Running BundleCleaner

  • Create conda environment using conda env create -f environment.yml.
  • Run BundleCleaner with the default parameters, python src/BundleCleanerV2.py -i test_bundles/AF_L.trk -o test_bundles/AF_L_proc.trk. Add -v flag for verbose output.
  • Python implementation of select bundle shape metrics defined in DSI Studio [1] are available at src/BundleInfo.py (original implementation).
  • Sample bundle from processed PPMI data for testing is provided at test_bundles/AF_L.trk.
Before Cleaning
AF_L before cleaning
After Cleaning
AF_L after cleaning

Cite our work

This work was accepted to the MICCAI 2023 CDMRI workshop. Preprint available at https://www.biorxiv.org/content/10.1101/2023.08.19.553990v1.

@misc{feng_bundlecleaner_2023,
	title = {{BundleCleaner}: {Unsupervised} {Denoising} and {Subsampling} of {Diffusion} {MRI}-{Derived} {Tractography} {Data}},
	copyright = {All rights reserved},
	shorttitle = {{BundleCleaner}},
	url = {https://www.biorxiv.org/content/10.1101/2023.08.19.553990v1},
	doi = {10.1101/2023.08.19.553990},
	language = {en},
	urldate = {2023-08-21},
	publisher = {bioRxiv},
	author = {Feng, Yixue and Chandio, Bramsh Q. and Villalon-Reina, Julio E. and Thomopoulos, Sophia I. and Joshi, Himanshu and Nair, Gauthami and Joshi, Anand A. and Venkatasubramanian, Ganesan and John, John P. and Thompson, Paul M.},
	month = aug,
	year = {2023},
  note = {Accepted to MICCAI 2023 CDMRI Workshop.}
}

References

[1] F.-C. Yeh, “Shape analysis of the human association pathways,” NeuroImage, vol. 223, p. 117329, Dec. 2020, doi: 10.1016/j.neuroimage.2020.117329.

[2] B. Q. Chandio et al., “Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations,” Sci Rep, vol. 10, no. 1, p. 17149, Dec. 2020, doi: 10.1038/s41598-020-74054-4.