tianyu0207/weakly-polyp
[MICCAI'22] Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection.
This project helps medical professionals or researchers automatically identify frames containing polyps within colonoscopy videos. You provide colonoscopy video data, and it outputs detections of specific frames that indicate the presence of polyps, making it easier to pinpoint areas of concern. This tool is designed for medical researchers or clinical practitioners focused on gastrointestinal endoscopy and pathology.
Use this if you need to efficiently detect and localize polyps in colonoscopy video footage, especially when manual frame-by-frame review is too time-consuming.
Not ideal if you require real-time, on-device detection during live endoscopy procedures or are working with still images rather than video sequences.
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43
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5
Language
Python
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Last pushed
Nov 12, 2025
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