Hausdorff distance loss support #6993
Comments
wyli
pushed a commit
that referenced
this issue
Sep 19, 2023
Integrating an existing implementation publicly available on GitHub by Patryk Rygiel into the MONAI framework. Fixes #6993. ### Description Hausdorff distance is widely used in evaluating medical image segmentation methods. Adding an objective/loss function directly to optimize this distance can be instrumental in optimizing this score [1]. <center><img src="https://upload.wikimedia.org/wikipedia/commons/2/21/Hausdorff_distance_sample.svg" alt="Hausdorff Distance"></center> An existing implementation is [publicly available on GitHub](https://github.com/PatRyg99/HausdorffLoss) by [Patryk Rygiel](https://github.com/PatRyg99), although it might take some engineering work to integrate within the MONAI framework. I was able to train a 3D segmentation model successfully using MONAI's SwinUNETR with this implementation and I would like to contribute the code for this loss so that it's more widely available and easier to integrate with MONAI-based repositories. **References**: [1] Karimi, D., & Salcudean, S. E. (2019). [Reducing the Hausdorff distance in medical image segmentation with convolutional neural networks](https://ieeexplore.ieee.org/abstract/document/8767031?casa_token=OGugo3jEuXQAAAAA:y5fp0CuZiEWlbx8FS4XKHu43Wi_W7albLeIAjsnZ1c-IlTpJmEFJUgoMlKl_taSYuBpcPyCvtTMe). IEEE Transactions on medical imaging, 39(2), 499-513. ### Types of changes <!--- Put an `x` in all the boxes that apply, and remove the not-applicable items --> - [x] Non-breaking change (fix or new feature that would not break existing functionality). - [ ] Breaking change (fix or new feature that would cause existing functionality to change). - [x] New tests added to cover the changes. - [x] Integration tests passed locally by running `./runtests.sh -f -u --net --coverage`. - [x] Quick tests passed locally by running `./runtests.sh --quick --unittests --disttests`. - [x] In-line docstrings updated. - [x] Documentation updated, tested `make html` command in the `docs/` folder. --------- Signed-off-by: Imad Toubal <imad.toubal@gmail.com>
|
Looks like I have forgotten to include the parameter alpha in the constructor method docstring. Do you recommend using this issue to make a PR to fix that? |
|
sure, thanks, please feel free to create PRs, if that's done in the next 10 hours we can still include it in v1.3 otherwise it'll be released in the future versions |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Hausdorff distance is widely used in evaluating medical image segmentation methods. Adding an objective/loss function directly to optimize this distance can be instrumental in optimizing this score [1].
An existing implementation is publicly available on GitHub by Patryk Rygiel, although it might take some engineering work to integrate within the MONAI framework.
I was able to train a 3D segmentation model successfully using MONAI's SwinUNETR with this implementation and I would like to contribute the code for this loss so that it's more widely available and easier to integrate with MONAI-based repositories.
References:
[1] Karimi, D., & Salcudean, S. E. (2019). Reducing the Hausdorff distance in medical image segmentation with convolutional neural networks. IEEE Transactions on medical imaging, 39(2), 499-513.
The text was updated successfully, but these errors were encountered: