Video Capsule Endoscopy

Video capsule endoscopy (VCE) is a minimally invasive technique for examining the gastrointestinal tract, but analysis of the resulting videos is time-consuming and requires expertise. Current research focuses on applying artificial intelligence, particularly convolutional neural networks (CNNs) and deep reinforcement learning, to automate tasks such as landmark detection, bleeding region segmentation, and even controlling the capsule's movement for optimal image acquisition. These AI-driven advancements aim to improve diagnostic accuracy, reduce analysis time, and ultimately enhance the efficiency and accessibility of VCE for patients and clinicians. The development of large, well-annotated datasets is also crucial for training and validating these AI models.