Autonomous surgical phase recognition on endoscopic camera images

At large, the desire of the Mitacs Research Grant is to gain understanding of surgery as a new field of science, dubbed Surgical Data Science (SDS), and to provide computer knowledge compatible robot system development through ontology driven Surgical Process Modeling (SPM) and Deep Learning (DL) methods, which can lead to autonomous surgical phase detection-based clinical systems. Surgical phase detection is a key challenge in SDS to create decision making support in the Operating Room. The overall objective is the development of autonomous surgical phase detection methods with SDM for laparoscopic hysterectomy (LH) procedures, based mainly on the endoscopic video data. All data used in the study is anonymized, publicly available, and surgically-annotated.

Faculty Supervisor:

Gabor Fichtinger

Student:

Partner:

Óbuda University

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology

University:

Queen's University

Program: