BrainMaGe
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CBICA
Brain extraction in presence of abnormalities, using single and multiple MRI modalities
According to dependabot:  Link to patch: https://github.com/pytorchlightning/pytorch-lightning/commit/8b7a12c52e52a06408e9231647839ddb4665e8ae PyTorch lightning 1.6.1 is already out [[ref](https://github.com/PyTorchLightning/pytorch-lightning/tree/1.6.1)] which should contain this fix, but making any change in dependencies would require testing.
Bumps [pytorch-lightning](https://github.com/Lightning-AI/lightning) from 0.8.1 to 1.6.0. Release notes Sourced from pytorch-lightning's releases. PyTorch Lightning 1.6: Support Intel's Habana Accelerator, New efficient DDP strategy (Bagua), Manual Fault-tolerance, Stability and Reliability. The...
![dependabot[bot] avatar](https://avatars.githubusercontent.com/in/29110?v=4 "dependabot[bot] avatar"){kind=avatar}
What changes would be required if the project were to run on Windows 10?
All of my images are unit volume. RAS orientation. BTW: I've tried RAS per documentation and also RAI and see no difference. I'm getting reasonably good masks running `python ../BrainMaGe/brain_mage_single_run...
This addresses issue #18 by updating PyTorch lightning code, adding black, and creating a faster API for inference using the Modality agnostic model.
Some minor updates in code for easier readability.
This PR fixes a bug where patient[0] was an int, causing a TypeError when used with os.path.join and string concatenation. Casting to str resolves the issue.
Bumps [pytorch-lightning](https://github.com/Lightning-AI/lightning) from 0.8.1 to 2.4.0. Release notes Sourced from pytorch-lightning's releases. Lightning v2.4 Lightning AI :zap: is excited to announce the release of Lightning 2.4. This is mainly a...