3 papers
cs.CV2025
Temporally-Aware Supervised Contrastive Learning for Polyp Counting in Colonoscopy
Luca Parolari, Andrea Cherubini, Lamberto Ballan +1
Automated polyp counting in colonoscopy is a crucial step toward automated procedure reporting and quality control, aiming to enhance the cost-effectiveness of colonoscopy screenin…
cs.CV2025
A Temporal Convolutional Network-Based Approach and a Benchmark Dataset for Colonoscopy Video Temporal Segmentation
Carlo Biffi, Giorgio Roffo, Pietro Salvagnini +1
Following recent advancements in computer-aided detection and diagnosis systems for colonoscopy, the automated reporting of colonoscopy procedures is set to further revolutionize c…
cs.CV2025
Towards Polyp Counting In Full-Procedure Colonoscopy Videos
Luca Parolari, Andrea Cherubini, Lamberto Ballan +1
Automated colonoscopy reporting holds great potential for enhancing quality control and improving cost-effectiveness of colonoscopy procedures. A major challenge lies in the automa…