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Project: Evaluation of AI methods for MRI segmentation on IDC data #1132

Closed ccosmin97 closed 4 months ago

ccosmin97 commented 4 months ago

Draft Status

Draft - team will hold off on page creation

Category

Segmentation / Classification / Landmarking

Presenter Location

In-person

Key Investigators

Project Description

We previously studied the application of a contrast-agnostic approach for MRI/CT abdomen organs segmentation, based on the generation of synthetic data. This synthetic data was then further used as a training set for a fully-supervised U-Net network. Since this study was performed, other methods aiming to segment MR abdominal organs have been published. Our goal is to evaluate these new methods on IDC MR abdominal-focused data and see how it compares to our method.

Objective

  1. Evaluate performance of MR abdominal organs methods on IDC data.
  2. Get feedback on our own method.

Approach and Plan

  1. Select a subset of IDC MR abdominal-focused IDC data.
  2. Create evaluation notebooks for newly published methods on this subset.
  3. Compare to our method.

Progress and Next Steps

  1. Describe specific steps you have actually done.

Illustrations

No response

Background and References

sjh26 commented 4 months ago

Hi @ccosmin97 , this is currently marked as a draft. If it is ready to go please let us know in a comment and we will get the page created

ccosmin97 commented 4 months ago

Hi @sjh26, yes sorry for the delay, the draft is ready!

github-actions[bot] commented 4 months ago

Project Page Pull Request Creation

:white_check_mark: COMPLETED: See https://github.com/NA-MIC/ProjectWeek/pull/1143