Skip to content

Latest commit

 

History

History
22 lines (13 loc) · 796 Bytes

README.md

File metadata and controls

22 lines (13 loc) · 796 Bytes

Omni-supervised domain adversarial training for WM hyperintensity segmentation

Code for implementation

Paper accepted at IEEE International Symposium for Biomedical Imaging (ISBI) 2022 (DOI to be updated soon)

Paper title: 'Omni-supervised domain adversarial training for white matter hyperintensity segmentation in the UK Biobank'

This is a preliminary version of the code. Contact: vaanathi.sundaresan@ndcn.ox.ac.uk.

Software Versions

Python 3.6.6 Pytorch 1.5.0

Code supplied for training of the model under uniform sampling setting and corresponding model prediction.

The baseline model used in this work is available at https://git.fmrib.ox.ac.uk/vaanathi/truenet.

If you use code from this repository please cite:

Citation details to be updated soon.