Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images

Author:

Zhou Yue,Chen HoujinORCID,Li Yanfeng,Liu Qin,Xu XuanangORCID,Wang Shu,Yap Pew-Thian,Shen Dinggang

Funder

Major Scientific and Technological Innovation Project of Shandong Province

National Natural Science Foundation of China

China Scholarship Council

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference58 articles.

1. Deep learning approaches for data augmentation and classification of breast masses using ultrasound images;Al-Dhabyani;Int. J. Adv. Comput. Sci. Appl.,2019

2. Boundary regularized convolutional neural network for layer parsing of breast anatomy in automated whole breast ultrasound;Bian,2017

3. Time to surgery and breast cancer survival in the united states;Bleicher;JAMA Oncol.,2016

4. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Bray;CA,2018

5. Screening breast ultrasound: past, present, and future;Brem;Am. J. Roentgenol.,2015

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