A deep learning method for classifying mammographic breast density categories-Reference-Cited by-同舟云学术

A deep learning method for classifying mammographic breast density categories

Published:2017-12-22 Issue:1 Volume:45 Page:314-321
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Mohamed Aly A.¹,Berg Wendie A.¹²,Peng Hong³,Luo Yahong⁴,Jankowitz Rachel C.²⁵,Wu Shandong⁶

Affiliation:

1. Department of Radiology; University of Pittsburgh School of Medicine; 4200 Fifth Ave Pittsburgh PA 15260 USA

2. Magee-Womens Hospital of University of Pittsburgh Medical Center; 300 Halket St Pittsburgh PA 15213 USA

3. Department of Radiology; Chinese PLA General Hospital; 28 Fuxing Rd Haidian District Beijing 100853 China

4. Department of Radiology; Liaoning Cancer Hospital & Institute; 44 Xiaoheyan Rd Dadong District Shenyang City Liaoning 110042 China

5. Department of Medicine; School of Medicine; University of Pittsburgh; 4200 Fifth Ave Pittsburgh PA 15260 USA

6. Departments of Radiology, Biomedical Informatics, Bioengineering, and Computer Science; University of Pittsburgh; 4200 Fifth Ave Pittsburgh PA 15260 USA

Funder

National Institutes of Health

Radiological Society of North America

Pittsburgh Foundation

National Center for Advancing Translational Sciences

Publisher

Wiley

Subject

General Medicine

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/mp.12683/fullpdf

Reference39 articles.

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3. The quantitative analysis of mammographic densities;Byng;Phys Med Biol,1994

4. A longitudinal investigation of mammographic density: the multiethnic cohort;Maskarinec;Cancer Epidemiol Biomarkers Prev,2006

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