bupt-ai-cz/CAC-UNet-DigestPath2019
1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task. (MICCAI 2019) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
This project helps pathologists and medical researchers quickly identify and classify malignant tissue in colonoscopy images. By analyzing digital images of colon tissue, it automatically highlights suspicious areas and categorizes them, providing a detailed output for further review. This is ideal for those involved in cancer diagnostics and research, aiming to improve the efficiency and accuracy of identifying cancerous regions.
100 stars. No commits in the last 6 months.
Use this if you need an automated system to segment and classify malignant tissue from colonoscopy images for diagnostic support or research purposes.
Not ideal if you are looking for a tool to process non-medical images or require real-time, in-vivo analysis during a colonoscopy procedure.
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Feb 18, 2023
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