Transfer learning for automatic joint segmentation of thyroid and breast lesions from ultrasound images.

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第一作者： Jinlian,Ma

第一单位： School of Microelectronics, Shandong University, Jinan, China.;Shenzhen Research Institute of Shandong University, A301 Virtual University Park in South District of Shenzhen, Shenzhen, China.;State Key Lab of CAD&CG, College of Computer Science and Technology, Zhejiang University, Hangzhou, China.

作者： Jinlian,Ma ^[1] ; Lingyun,Bao ^[2] ; Qiong,Lou ^[3] ; Dexing,Kong ^[4]

作者单位： School of Microelectronics, Shandong University, Jinan, China.;Shenzhen Research Institute of Shandong University, A301 Virtual University Park in South District of Shenzhen, Shenzhen, China.;State Key Lab of CAD&CG, College of Computer Science and Technology, Zhejiang University, Hangzhou, China. ^[1] Department of Ultrasound, Hangzhou First Peoples Hospital, Zhejiang University, Hangzhou, China. ^[2] School of Science, Zhejiang University of Sciences and Technology, Hangzhou, China. ^[3] School of Mathematical Sciences, Zhejiang University, Hangzhou, China. majinlian111@163.com. ^[4]

关键词 Densely connected convolutional network Lesions Segmentation Transfer learning Ultrasound image

主题词乳房(Breast);人类(Humans);图像处理, 计算机辅助(Image Processing, Computer-Assisted);甲状腺结节(Thyroid Nodule);超声检查(Ultrasonography)

DOI 10.1007/s11548-021-02505-y

PMID 34881409

发布时间 2022-01-25

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