Deep learning based classification of breast tumors with shear-wave elastography-Reference-Cited by-同舟云学术

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Deep learning based classification of breast tumors with shear-wave elastography

Published:2016-12 Issue: Volume:72 Page:150-157
ISSN:0041-624X
Container-title:Ultrasonics
language:en
Short-container-title:Ultrasonics

Author:

Zhang Qi,Xiao Yang,Dai Wei,Suo Jingfeng,Wang Congzhi,Shi Jun,Zheng Hairong

Funder

National Natural Science Foundation of China

Shanghai Natural Science Fund for Youth Scholars

Publisher

Elsevier BV

Subject

Acoustics and Ultrasonics

Reference47 articles.

1. Breast cancer facts and figures 2013–2014;DeSantis;Am. Cancer Soc.,2013

2. WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 2: breast;Barr;Ultrasound. Med. Biol.,2015

3. Quantitative maximum shear-wave stiffness of breast masses as a predictor of histopathologic severity;Berg;Am. J. Roentgenol.,2015

4. Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses;Berg;Radiology,2012

5. ShearWave (TM) elastography BE1 multinational breast study: additional SWE (TM) features support potential to downgrade BI-RADS (R)-3 lesions;Schafer;Ultraschall Med.,2013

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