Deep learning modeling using normal mammograms for predicting breast cancer risk-Reference-Cited by-同舟云学术

Deep learning modeling using normal mammograms for predicting breast cancer risk

Published:2019-11-19 Issue:1 Volume:47 Page:110-118
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Arefan Dooman¹,Mohamed Aly A.¹,Berg Wendie A.¹²,Zuley Margarita L.¹²,Sumkin Jules H.¹²,Wu Shandong³

Affiliation:

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

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

3. Departments of Radiology, Biomedical Informatics, Bioengineering, and Intelligent Systems Program University of Pittsburgh 4200 Fifth Ave Pittsburgh PA15260USA

Funder

National Institutes of Health

Radiological Society of North America

National Science Foundation

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.13886

Reference46 articles.

1. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c‐means clustering and support vector machine segmentation

2. A first evaluation of breast radiological density assessment by QUANTRA software as compared to visual classification

3. AlainG BengioY.Understanding intermediate layers using linear classifier probes arXiv preprint arXiv:1610.01644 (2016).

4. Mammographic Density and the Risk and Detection of Breast Cancer

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