This is a collection of research papers for Surgical AI. And the repository will be continuously updated to track the frontier of the topic.
Welcome to contribute and star!
format:
- [title](paper link) [links]
- author1, author2, and author3...
- Institute
- publish
- keyword
- code
- experiment environments and datasets
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A vision transformer for decoding surgeon activity from surgical videos
- Author: Dani Kiyasseh, Runzhuo Ma, Taseen F. Haque, Brian J. Miles, Christian Wagner, Daniel A. Donoho, Animashree Anandkumar & Andrew J. Hung
- Institute: California Institute of Technology & University of Southern California
- Publish: Nature Biomedical Engineering
- Keyword: Transformer, Surgeon activity, Surgeon video
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The impact of inconsistent human annotations on AI driven clinical decision making
- Author: Aneeta Sylolypavan, Derek Sleeman, Honghan Wu & Malcolm Sim
- Institute: University College London
- Publish: npj Digital Medicine
- Keyword: human annotations, clinical decision making
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Human visual explanations mitigate bias in AI-based assessment of surgeon skills
- Author: Dani Kiyasseh, Jasper Laca, Taseen F. Haque, Maxwell Otiato, Brian J. Miles, Christian Wagner, Daniel A. Donoho, Quoc-Dien Trinh, Animashree Anandkumar & Andrew J. Hung
- Institute: California Institute of Technology & University of Southern California
- Publish: npj Digital Medicine
- Keyword: Human visual explanations, assessment of surgeon skills
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- Author: Cong Gao, Benjamin D. Killeen, Yicheng Hu, Robert B. Grupp, Russell H. Taylor, Mehran Armand & Mathias Unberath
- Institute: California Institute of Technology & University of Southern California
- Publish: Nature Machine Intelligence
- Keyword: Synthetic data, X-ray image analysis
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PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment
- Institute: Oxford Universiy
- Publish: Nature Scientific data
- Keyword: 3761 images dataset, polyp detection and segmentation
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Image Compositing for Segmentation of Surgical Tools without Manual Annotations
- Institute: University College London
- Publish: IEEE TMI
- Keyword: 514 manually labeled images from 20 surgical procedures, 100K labeled synthetic images, surgical tool segmentation