Stereo Endoscopic

Stereo endoscopic imaging focuses on reconstructing three-dimensional scenes from pairs of endoscopic videos, primarily to improve surgical planning and execution. Current research emphasizes developing robust and efficient algorithms, often employing neural networks (including neural radiance fields and convolutional neural networks) to address challenges like tissue deformation, low-resolution images, and accurate instrument segmentation. These advancements are significantly impacting minimally invasive surgery by enabling improved visualization, real-time scene understanding, and ultimately, enhanced surgical precision and patient outcomes.