Colonoscopy Reconstruction

Colonoscopy reconstruction aims to create three-dimensional models of the colon from endoscopic video, improving visualization and potentially aiding polyp detection and colorectal cancer prevention. Current research focuses on refining neural network architectures, such as Neural Radiance Fields (NeRFs) and related methods, to overcome challenges like inconsistent colon geometry, limited camera viewpoints, and variations in lighting and reflectivity. These advancements leverage depth estimation, surface normal information, and novel view synthesis to generate more accurate and complete 3D reconstructions, ultimately improving the diagnostic capabilities of colonoscopy. The resulting improvements in visualization and coverage estimation have the potential to significantly enhance the accuracy and effectiveness of colorectal cancer screening.