マサムネ　ケン   MASAMUNE Ken   正宗　賢    所属   研究施設 研究施設    職種   教授
論文種別	原著
言語種別	英語
査読の有無	査読あり
表題	Automatic 3D landmarking model using patch-based deep neural networks for CT image of oral and maxillofacial surgery
掲載誌名	正式名：The International Journal of Medical Robotics and Computer Assisted Surgery ISSNコード：1478-596X
掲載区分	国外
出版社	© 2020 John Wiley & Sons, Ltd.
巻・号・頁	16(3),pp.e2093
著者・共著者	MA Qingchuan†, KOBAYASHI Etsuko, FAN ,Bowen , NAKAGAWA Keiichi , SAKUMA Ichiro, MASAMUNE Ken, SUENAGA Hideyuki*
発行年月	2020/06
概要	Background Manual landmarking is a time consuming and highly professional work. Although some algorithm‐based landmarking methods have been proposed, they lack flexibility and may be susceptible to data diversity. Methods The CT images from 66 patients who underwent oral and maxillofacial surgery (OMS) were landmarked manually in MIMICS. Then the CT slices were exported as images for recreating the 3D volume. The coordinate data of landmarks were further processed in Matlab using a principal component analysis (PCA) method. A patch‐based deep neural network model with a three‐layer convolutional neural network (CNN) was trained to obtain landmarks from CT images.
DOI	10.1002/rcs.2093
PMID	32065718