Supervised learning has been the cornerstone of many successful medical imaging
applications. However, its reliance on large labeled datasets poses significant challenges …

Abstract Wireless Capsule Endoscopy is a medical procedure that uses a small, wireless
camera to capture images of the inside of the digestive tract. The identification of the …

While deep learning has displayed excellent performance in a broad spectrum of application
areas, neural networks still struggle to recognize what they have not seen, ie, out-of …

Endoscopy, a widely used medical procedure for examining the gastrointestinal (GI) tract to
detect potential disorders, poses challenges in manual diagnosis due to non-specific …

Wireless capsule endoscopy is a non-invasive medical imaging modality used for
diagnosing and monitoring digestive tract diseases. However, the analysis of images …

While the adoption of wireless capsule endoscopy (WCE) has been steadily increasing, its
primary application remains limited to observing the small intestine, with relatively less …

Medical image synthesis has emerged as a promising solution to address the limited
availability of annotated medical data needed for training machine learning algorithms in the …

Colorectal cancer (CRC), ranking third most prevalent cancer type, can be diagnosed with
the detection of polyps in the colon and rectum through endoscopic procedures facilitating …

Wireless Capsule Endoscopy (WCE) is a procedure to examine the human digestive system
for potential mucosal polyps, tumours, or bleedings using an encapsulated camera. This …

Colorectal cancer is the most common cancer with a second mortality rate. Polyp lesion is a
precursor symptom of colorectal cancer. Detection and removal of polyps can effectively …