オカモト　トシヒロ   OKAMOTO Toshihiro   岡本　俊宏    所属   医学部 医学科（東京女子医科大学病院）    職種   教授・基幹分野長
言語種別	英語
発表タイトル	Classification of Oral Cancer and Leukoplakia Using Oral Images and Deep Learning with Multi-Scale Random Crop Self-Training
会議名	14th NameInternational Conference on Pattern Recognition Applications and Methods
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	◎HAMADA Itsuki, OHKAWAUCHI Takaaki, AOSHIMA Chisa, YOSHIMITSU Kitaro, KAIBUCHI Nobuyuki, OKAMOTO Toshihiro, SAKAGUCHI Katsuhisa, OHYA Jun
発表年月日	2025/02/23
開催地 （都市, 国名）	Portugal
開催期間	2025/02/23～2025/02/25
学会抄録	Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods 780-787 2025
概要	This paper proposes Multi-Scale Random Crop Self-Training (MSRCST) for classifying oral cancers and leukoplakia using oral images acquired by our dermoscope. MSRCST comprises the following three key modules: (1) Multi-Scale Random Crop, which extracts image patches at various scales from high-resolution images, preserving both local details and global contextual information essential for accurate classification, (2) Selection based on Confidence, which employs a teacher model to assign confidence scores to each cropped patch, selecting only those with high confidence for further training and ensuring the model focusing on diagnostically relevant features, (3) Iteration of Self-training, which iteratively retrains the model using the selected high-confidence, pseudo-labeled data, progressively enhancing accuracy. In our experiments, we applied MSRCST to classify images of oral cancer and leukoplakia. When combined with MixUp data augmentation, MSRCST achieved an average classification accuracy of 71.71%, outperforming traditional resizing and random cropping methods.