Foundation models have exhibited remarkable success in various applications, such as
disease diagnosis and text report generation. To date, a foundation model for endoscopic …

Surgical scene perception via videos is critical for advancing robotic surgery, telesurgery,
and AI-assisted surgery, particularly in ophthalmology. However, the scarcity of diverse and …

Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges
such as scalability and acceptance. These challenges include data availability, biased …

Wireless capsule endoscopy (WCE) is a painless and non-invasive diagnostic tool for
gastrointestinal (GI) diseases. However, due to GI anatomical constraints and hardware …

Automatic and accurate medical image segmentation is a crucial step for clinical diagnosis
and treatment planning of diseases. The advanced convolutional neural network (CNN) …

Abstract Wireless Capsule Endoscopy (WCE) is highly valued for its non-invasive and
painless approach, though its effectiveness is compromised by uneven illumination from …

Abstract Domain gaps are among the most relevant roadblocks in the clinical translation of
machine learning (ML)-based solutions for medical image analysis. While current research …

Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large
number of highly lethal GI cancers. Early GI cancer precursors are often missed during the …

Gastrointestinal cancer is the leading cause of cancer-related incidence and death.
Therefore, it is important to develop a novel computer-aided diagnosis system for early …

In this paper, a novel method is proposed to detect common abnormalities in Wireless
Capsule Endoscopy (WCE) video frames including Lymphoid Hyperplasia, ulcer, and …