Summary of Verse: Integrating Multiple Queries As Prompts For Versatile Cardiac Mri Segmentation, by Bangwei Guo et al.
VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation
by Bangwei Guo, Meng Ye, Yunhe Gao, Bingyu Xin, Leon Axel, Dimitris Metaxas
First submitted to arxiv on: 20 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the challenge of accurately segmenting cardiac structures from magnetic resonance imaging (MRI) scans. Existing automatic segmentation methods require manual corrections by experts, particularly in complex regions like the basal and apical parts of the heart. To overcome these limitations, the authors propose VerSe, a Versatile Segmentation framework that unifies automatic and interactive segmentation through multiple queries. The key innovation lies in jointly learning object and click queries as prompts for a shared segmentation backbone. VerSe supports both fully automatic segmentation and interactive mask refinement, offering significant improvements in performance and efficiency over existing methods on cardiac MRI and out-of-distribution medical imaging datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us better understand how to accurately identify parts of the heart from MRI scans. Right now, computers can only do this job with some help from humans. The authors are trying to change that by creating a new way for computers to learn what they need to know to do this task on their own. They call it VerSe and it lets computers do some parts of the job without human help. This makes things faster and more accurate. The researchers tested VerSe on real MRI scans and found that it works well. |
Keywords
» Artificial intelligence » Mask
