Among the world's most common cancers, colorectal cancer is the third most severe form of
cancer. Early polyp detection reduces the risk of colorectal cancer, vital for effective …

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 …

Colonoscopy is widely recognised as the gold standard procedure for the early detection of
colorectal cancer (CRC). Segmentation is valuable for two significant clinical applications …

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

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

Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst
most polyps are benign, the polyp's number, size and surface structure are linked to the risk …

Colonoscopy is the gold standard for examination and detection of colorectal polyps.
Localization and delineation of polyps can play a vital role in treatment (eg, surgical …

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in
their size, appearance, and location makes the detection of polyps challenging. Moreover …

Integrating Stereo Imaging technology into medical diagnostics and surgeries marks a
significant revolution in medical sciences. This advancement gives surgeons and physicians …

The human gastrointestinal (GI) tract is an important part of the body. According to World
Health Organization (WHO) research, GI tract infections kill 1.8 million people each year. In …