Name
Title | ||
|---|---|---|
Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review |
Abstract | ||
|---|---|---|
•Studies are summarized to explore deep learning can be best integrated into breast cancer screening workflows using DBT.•This survey is conducted for the foundations of deep learning methods in diagnostic and non- diagnostic DBT images.•The limitations of integrating deep learning into clinical practice and the opportunities are identified in this paper. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.media.2021.102049 | Medical Image Analysis |
Keywords | DocType | Volume |
Digital breast tomosynthesis,Deep learning,Review | Journal | 71 |
ISSN | Citations | PageRank |
1361-8415 | 1 | 0.36 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Bai | 1 | 1 | 0.36 |
| Russell Posner | 2 | 1 | 0.36 |
| Tianyu Wang | 3 | 120 | 30.07 |
| Clifford Yang | 4 | 6 | 1.82 |
| Sheida Nabavi | 5 | 18 | 8.68 |