Detecting Asymmetric Patterns and Localizing Cancers on Mammograms

Detecting Asymmetric Patterns and Localizing Cancers on Mammograms

Summary: One in eight women develops invasive breast cancer in her lifetime. The frontline protection against this disease is mammography. While computer-assisted diagnosis algorithms have made great progress in generating reliable global predictions, few focus on simultaneously producing regions of...

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Bibliographic Details
Main Authors: Yuanfang Guan, Xueqing Wang, Hongyang Li, Zhenning Zhang, Xianghao Chen, Omer Siddiqui, Sara Nehring, Xiuzhen Huang
Format: Article
Language:English
Published: Elsevier 2020-10-01
Series:Patterns
Subjects:
breast cancer
digital mammography
asymmetry
deep learning
computer-assisted diagnosis
Online Access:http://www.sciencedirect.com/science/article/pii/S2666389920301409

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http://www.sciencedirect.com/science/article/pii/S2666389920301409

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