マサムネ　ケン   Masamune Ken   正宗　賢    所属   医学研究科 医学研究科 (医学部医学科をご参照ください)    職種   教授
言語種別	英語
発表タイトル	Detecting and Tracking Surgical Tools for Recognizing Phases of the Awake Brain Tumor Removal Surgery
会議名	the 8th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2019)
学会区分	国際学会及び海外の学会
発表形式	口頭
講演区分	一般
発表者・共同発表者	FUJIE Hiroki†, HIRATA Keiju , HORIGOME Takahiro , NAGAHASHI Hiroshi , OHYA Jun, TAMURA Manabu, MASAMUNE Ken, MURAGAKI Yoshihiro
発表年月日	2019/02/19
開催地 （都市, 国名）	Prague, Czech Republic
学会抄録	In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2019) 190-199
概要	Keywords: Computer Vision, Multiple Object Tracking, Detection, Data Association, Convolutional Neural Network, Data Augmentation, Awake Brain Tumor Removal Surgery. Abstract: In order to realize automatic recognition of surgical processes in surgical brain tumor removal using microscopic camera, we propose a method of detecting and tracking surgical tools by video analysis. The proposed method consists of a detection part and tracking part. In the detection part, object detection is performed for each frame of surgery video, and the category and bounding box are acquired frame by frame. The convolution layer strengthens the robustness using data augmentation (central cropping and random erasing). The tracking part uses SORT, which predicts and updates the acquired bounding box corrected by using Kalman Filter; next, the object ID is assigned to each corrected bounding box using the Hungarian algorithm. The accuracy of our proposed method is very high as follows. As a result of experiments on spatial detection. the mean average precision is 90.58%. the mean accuracy of frame label detection is 96.58%. These results are very promising for surgical phase recognition.