Contrastive transformer-based multiple instance learning for weakly supervised polyp frame detection

• Main Authors: YU, Tian, PANG, Guansong, LIU, Fengbei, LIU, Yuyuan, WANG, Chong, CHEN, Yuanhong, VERJANS, Johan, CARNEIRO, Gustavo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Polyp detection; Colonoscopy; Weakly-supervised learning; Video anomaly detection; Vision transformer; Artificial Intelligence and Robotics; Medical Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/7549; https://ink.library.smu.edu.sg/context/sis_research/article/8552/viewcontent/2203.12121.pdf
• Institution: Singapore Management University

Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutive video frames, and ii) lack knowledge about the polyps. Consequently, they often have high detection errors, especially...