Endoscopic Imaging

Endoscopic imaging research focuses on improving the quality and information extracted from images obtained during minimally invasive procedures. Current efforts concentrate on developing advanced deep learning models, including transformer-based networks and convolutional neural networks, to address challenges like image segmentation, workflow recognition, and artifact removal. These advancements aim to enhance diagnostic accuracy, improve surgical precision, and ultimately lead to better patient outcomes by enabling more effective analysis of endoscopic data. The development of large, publicly available datasets is also a key focus, facilitating the training and validation of these sophisticated algorithms.