Deep Learning Breast Density Estimation
Deep Learning Breast Density Estimation is a computational methodology that employs deep neural networks to automatically quantify breast tissue density from medical imaging data, distinguishing itself from traditional radiologic and statistical approaches by leveraging hierarchical feature representations learned directly from large datasets.
31
Publications
2.1K
Citations
217
Authors
88
Institutions
Publications per year
2017–2026
30
Parents
31
Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation
Constance D. Lehman, Adam Yala, Tal Schuster et al. · Radiology · 2018 · 289 citations
Babita Pandey, Devendra Kumar Pandey, Brijendra Pratap Mishra et al. · Journal of King Saud University - Computer and Information Sciences · 2021 · 115 citations · Full text
Fully Automated Breast Density Segmentation and Classification Using Deep Learning
Nasibeh Saffari, Hatem A. Rashwan, Mohamed Abdel‐Nasser et al. · Diagnostics · 2020 · 90 citations · Full text
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88
Massachusetts General Hospital
Boston, United States
3 h-index
17 publications
2.5K citations
University of Pittsburgh
Pittsburgh, United States
2 h-index
6 publications
418 citations

Sun Yat-sen University
Guangzhou, China
2 h-index
4 publications
152 citations
University of Michigan
Ann Arbor, United States
2 h-index
13 publications
515 citations
Tzu Chi University
Hualien City, Taiwan
1 h-index
3 publications
60 citations
University of Pittsburgh Medical Center
Pittsburgh, United States
1 h-index
2 publications
118 citations
Liaoning Cancer Hospital & Institute
Shenyang, China
1 h-index
1 publications
59 citations
University of Copenhagen
Copenhagen, Denmark
1 h-index
5 publications
2.2K citations
1–8 of 88
3 publications · 131 citations
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JMI · 2 publications · 110 citations
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2 publications · 52 citations
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2 publications · 115 citations
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2 publications · 79 citations
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