Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Pseudo DICE and traning/testing losses not improving #2584

Open
CYH16 opened this issue Nov 5, 2024 · 0 comments
Open

Pseudo DICE and traning/testing losses not improving #2584

CYH16 opened this issue Nov 5, 2024 · 0 comments

Comments

@CYH16
Copy link

CYH16 commented Nov 5, 2024

Hi, thank you for this wonderful model. It helped me a lot with several projects.

However, in one of my recent projects where I tried to implement nnUNet to segment ureteral stone from noncontrast abdominal CT, the dice was constantly 0.0 and the traning/testing losses were oscillating. I don't think it was because small segments compared with the whole images since nnUNet performed well in another project where the segments were also small.

Are there any other possibilities that I can check on or improve? Or if I need to provide some relevant information, please let me know.

Again, thanks a lot for this wonderful model.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant