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

Automated tool to detect artefacted image (can use the 'exclude.yaml' files) #22

Open
jcohenadad opened this issue Mar 13, 2024 · 2 comments

Comments

@jcohenadad
Copy link
Member

jcohenadad commented Mar 13, 2024

As we are building our internal MRI database, we progressively list the images that have excessive artifacts in the file exclude.yaml. We should exploit that information and train a model that automatically detects if an images has excessive artifact. When processing large cohorts, that information would be very useful to have.

Todo: make sure that our exclude.yaml uses the same vocabulary to identify artifacts.

@plbenveniste
Copy link

That's a very nice and useful idea. With the numerous problematic images in CanProCo, I think it can easily be trained (at least on the PSIR contrast : examples here).

@valosekj
Copy link
Member

Great idea! Cross-referring #5.

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

No branches or pull requests

3 participants