Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and
displays to electronics connecting configurable illumination and actuation systems for …

International challenges have become the de facto standard for comparative assessment of
image analysis algorithms. Although segmentation is the most widely investigated medical …

Semantic image segmentation is the process of labeling each pixel of an image with its
corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a …

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

Colonoscopy is considered the gold standard for detection of colorectal cancer and its
precursors. Existing examination methods are, however, hampered by high overall miss …

While the importance of automatic image analysis is continuously increasing, recent meta-
research revealed major flaws with respect to algorithm validation. Performance metrics are …

Methods based on convolutional neural networks have improved the performance of
biomedical image segmentation. However, most of these methods cannot efficiently …

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

Surgical skills are associated with clinical outcomes. To improve surgical skills and thereby
reduce adverse outcomes, continuous surgical training and feedback is required. Currently …