Review in Deep Learning for Polyp Detection and Classification in Colonoscopy (https://doi.org/10.1016/j.neucom.2020.02.123).

2021-MICCAI-Progressively Normalized Self-Attention Network for Video Polyp Segmentation

Official website for "Video Polyp Segmentation: A Deep Learning Perspective (MIR 2022)"

Colonoscopy polyps detection with CNNs

Official implementation of ColonSegNet: Real-Time Polyp Segmentation (Used in NVIDIA Clara Holoscan App for Polyp Segmentation)

Computational Endoscopy Platform (advanced deep learning toolset for analyzing endoscopy videos) [MICCAI'22, MICCAI'21, ISBI'21, CVPR'20]

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

TGANet: Text-guided attention for improved polyp segmentation [Early Accepted & Student Travel Award at MICCAI 2022]

TransResU-Net: Transformer based ResU-Net for Real-Time Colonoscopy Polyp Segmentation

GitHub repository for Medico automatic polyp segmentation challenge

Frontiers in Intelligent Colonoscopy [ColonSurvey | ColonINST | ColonGPT]

This is a repository for the project Detection of Polyps in Colonoscopy. We implement the pipeline for detecting and segmenting the polyps from the capsule endoscopy video feed.

Liver segmentation using Deep Learning on LiTS 2017 Dataset

Polyp segmentation tool utilizing U-Net for accurate medical image analysis, designed to enhance early detection and diagnosis of colorectal cancer. Features a user-friendly Streamlit web app for easy image processing and analysis, leveraging the Kvasir-SEG dataset for improved healthcare outcomes.

MICCAI 2019 Grand Challenge for Pathology - Digestive-System Pathological Segmentation Challenge

GitHub repository for the Kvasir-instrument dataset

Kvasir-SEG: A Segmented Polyp Dataset

A multi-centre polyp detection and segmentation dataset for generalisability assessment https://www.nature.com/articles/s41597-023-01981-y

In Testing - comments welcome. Tool to provide guidance on colonoscopic surveillance based on BSG/PHE/ACPGBI 2019 surveillance guidelines and BSG hereditary cancer guidelines.

TransRUPNet for Improved Out-of-Distribution Generalization in Polyp Segmentation (IEEE EMBC)