Automatic segmentation of female urine control anatomical elements and related structures in MRI images based on deep learning

Objective‍　‍To construct an automatic segmentation model to segment female urine control anatomy on MRI images based on deep learning methods in order to improve the segmentation efficiency and accuracy. Methods‍　‍A dataset comprising 49 female pelvic floor muscle MRI images [30 women with varying d...

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書誌詳細

出版年:	陆军军医大学学报
主要な著者:	ZHANG Ziqin, WU Yi, ZHANG Xiaoqin
フォーマット:	論文
言語:	中国語
出版事項:	Editorial Office of Journal of Army Medical University 2025-07-01
主題:	‍deep learning image segmentation intelligent assisted diagnosis nuclear magnetic resonance image
オンライン･アクセス:	https://aammt.tmmu.edu.cn/html/202406055.html