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Integrate MRSegmentator and DeepSpA models into mhub.ai

Key Investigators

• Felix Dorfner (Charité Universitätsmedizin Berlin, Germany)
• Hartmut Häntze (Charité Universitätsmedizin Berlin, Germany)
• Keno Bressem (Technical University of Munich, Germany)

Presenter location: In-person

Project Description

This project will aim to integrate two models into mhub.ai.

1. MRSegmentator:

• Is a segmentation model that can accurately segment 40 organs and structures in human MRI scans of the abdominal, pelvic and thorax regions. The model works on different sequence types, including T1- and T2-weighted, Dixon sequences and even CT images.
• Paper: https://arxiv.org/abs/2405.06463

2. DeepSpA:

• Is classification model that incorporates anatomical awareness to detect radiographic sacroiliitis. Detecting radiographic sacroiliitis plays an essential role in diagnosing and classifying axial Spondyloarthritis (axSpA).
• Paper: https://arxiv.org/abs/2405.07369

Objective

1. Objective: Working implementation of MRSegmentator into the mhub.ai platform.
2. Objective: Working implementation of DeepSpA into the mhub.ai platform

Approach and Plan

TBD

Progress and Next Steps

TBD

Illustrations

Illustrations of both models can be seen on their respective GitHub pages, linked below:

Background and References

MRSegmentator:

• Code: https://github.com/hhaentze/MRSegmentator
• Paper: https://arxiv.org/abs/2405.06463

DeepSpA:

• Code: https://github.com/FJDorfner/Anatomy-Aware-Classification-axSpA
• Paper: https://arxiv.org/abs/2405.07369