MASAMUNE Ken    Department   Research Institutes and Facilities, Research Institutes and Facilities    Position   Professor
Language	Japanese
Title	A study on Surgical Process and Procedure（or technique）Identification Method Using Pre‒ and Intra‒operative Information in Awake Surgery of Glioma
Conference	The 28th Annual Congress of Japan Society of Computer Aided Surgery
Conference Type	Nationwide Conferences
Presentation Type	Speech
Lecture Type	General
Date	2019/11/24
Society abstract	日本コンピュータ外科学会誌 21(4),339-340 2019
Summary	Abstract：During surgery for glioma, surgeon will resect a glioma based on experience and technique, by considering tumor position, brain function, and surrounding structure. The experience and technique of surgeon is implicit knowledge; the visualization of this knowledge is important for improvement and educational support to increase the quality of medical care. Therefore, we aim to visualize the knowledge by the identification and analysis of surgical processes, based on previous research1）. As a result, Visualization of implicit knowledge requires refinement of the model and visualization of the procedure. In this study, we propose of surgical processes model and identification method process using machine learning in awake surgery. First, we subdivided the process that includes the surgeonʼs procedure into 13 processes as the fourth layer in the previous 3 layered HHMM model. Seconds, we automatically extract the features using machine learning, image and signal processing. Finally, surgical processes are identified using the new features. The method has been evaluated on the past data. Accuracy of the identified processes was 63.2％. Feature extraction accuracy greatly affects identification accuracy. Therefore, more accurate extraction is necessary in the future. Our future work is development of surgical process analysis system to visualize of implicit surgical knowledge. Key words：Surgical process, Machine Learning, Modeling