• Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges 

      Jha, Debesh; Sharma, Vanshali; Banik, Debapriya; Bhattacharya, Debayan; Roy, Kaushiki; Hicks, Steven; Tomar, Nikhil Kumar; Thambawita, Vajira L B; Krenzer, Adrian; Ji, Ge-Peng; Poudel, Sahadev; Batchkala, George; Alam, Saruar; Ahmed, Awadelrahman M.A.; Trinh, Quoc-Huy; Khan, Zeshan; Nguyen, Tien-Phat; Shrestha, Shruti; Nathan, Sabari; Gwak, Jeonghwan Gwak; Jha, Ritika Kumari; Zhang, Zheyuan; Schlaefer, Alexander; Bhattacharjee, Debotosh; Bhuyan, M.K.; Das, Pradip K.; Fan, Deng-Ping; Parasa, Sravanthi; Ali, Sharib; Riegler, Michael Alexander; Halvorsen, Pål; de Lange, Thomas; Bagci, Ulas (Journal article; Tidsskriftartikkel; Peer reviewed, 2025-09-05)
      Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is ...