Summary of Surgplan++: Universal Surgical Phase Localization Network For Online and Offline Inference, by Zhen Chen et al.
SurgPLAN++: Universal Surgical Phase Localization Network for Online and Offline Inference
by Zhen Chen, Xingjian Luo, Jinlin Wu, Long Bai, Zhen Lei, Hongliang Ren, Sebastien Ourselin, Hongbin Liu
First submitted to arxiv on: 19 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 proposes a universal Surgical Phase Localization Network, called SurgPLAN++, to recognize surgical phases in videos. The existing studies focused on online recognition and lacked global context of the entire procedure. To overcome this challenge, SurgPLAN++ predicts phase segments across the entire video through phase proposals. For online analysis, it incorporates data augmentation to extend the streaming video into a pseudo-complete video. For offline analysis, it refines preceding predictions during each online inference step, improving the accuracy of phase recognition. The proposed method achieves remarkable performance in both online and offline modes, outperforming state-of-the-art methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps doctors analyze surgical videos better. Current methods are good at predicting what’s happening in a video as it happens, but they don’t do well when looking back at the whole procedure. To fix this, the authors created a new method called SurgPLAN++ that can look at the entire video and make accurate predictions about the different stages of surgery. This will be helpful for doctors who want to learn from past surgeries or study how procedures are performed. |
Keywords
» Artificial intelligence » Data augmentation » Inference
