Recent developments in deep learning have enabled data-driven algorithms that can reach
human-level performance and beyond. The development and deployment of medical image …

Image segmentation for video analysis plays an essential role in different research fields
such as smart city, healthcare, computer vision and geoscience, and remote sensing …

Computer-aided detection, localization, and segmentation methods can help improve
colonoscopy procedures. Even though many methods have been built to tackle automatic …

Abstract The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative
to address eminent problems in developing reliable computer aided detection and diagnosis …

We present a comprehensive analysis of the submissions to the first edition of the
Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step …

Joint visual and language modeling on large-scale datasets has recently shown good
progress in multi-modal tasks when compared to single modal learning. However …

Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an
effective screening technique, navigating an endoscope through the colon to detect polyps …

This article reviews deep learning applications in biomedical optics with a particular
emphasis on image formation. The review is organized by imaging domains within …

Accurate polyp segmentation is important for the diagnosis and treatment of colon cancer. In
recent years, efforts have been made to improve the encoder-decoder framework by using …

Artificial intelligence shows promise for clinical research in inflammatory bowel disease
endoscopy. Accurate assessment of endoscopic activity is important in clinical practice and …