Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study
Abstract Background To determine if mammographic features from deep learning networks can be applied in breast cancer to identify groups at interval invasive cancer risk due to masking beyond using traditional breast density measures. Methods Full-field digital screening mammograms acquired in our c...
Main Authors: | , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2019-06-01
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Series: | Cancer Imaging |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s40644-019-0227-3 |