Colonoscopy Video

Colonoscopy video analysis focuses on improving polyp detection and overall procedure understanding through automated image processing. Current research employs convolutional neural networks (CNNs), vision transformers, and recurrent neural networks (RNNs like BiLSTMs) to achieve tasks such as polyp detection, depth estimation for 3D reconstruction, and semantic parsing of video content to understand procedure flow. These advancements aim to enhance diagnostic accuracy, improve procedural efficiency, and ultimately contribute to earlier colorectal cancer detection and improved patient outcomes. The development of large, high-quality datasets, including those with paired 2D and 3D data, is crucial for training and validating these increasingly sophisticated algorithms.