Real-time estimation of the remaining surgery duration for cataract surgery using deep convolutional neural networks and long short-term memory

Abstract

Estimating the surgery length has the potential to be utilized as skill assessment, surgical training, or efficient surgical facility utilization especially if it is done in real-time as a remaining surgery duration (RSD). Surgical length reflects a certain level of efficiency and mastery of the surgeon in a well-standardized surgery such as cataract surgery. In this paper, we design and develop a real-time RSD estimation method for cataract surgery that does not require manual labeling and is transferable with minimum fine-tuning.

Bowen Wang

Specially-Appointed Researcher/Fellow

Liangzhi Li

Guest Assistant Professor

His research interests lie in deep learning, computer vision, robotics, and medical images.

Hajime Nagahara

Professor

He is working on computer vision and pattern recognition. His main research interests lie in image/video recognition and understanding, as well as applications of natural language processing techniques.