Reliable Breast Cancer Diagnosis with Deep Learning: DCGAN-Driven Mammogram Synthesis and Validity Assessment
Breast cancer imaging is paramount to quickly detecting and accurately evaluating the disease. The scarcity of annotated mammogram data presents a significant obstacle when building deep learning models that can produce reliable outcomes. This paper proposes a novel approach that utilizes deep convo...
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| Veröffentlicht in: | Applied Computational Intelligence and Soft Computing Jg. 2024; H. 1 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Hindawi
2024
John Wiley & Sons, Inc Wiley |
| Schlagworte: | |
| ISSN: | 1687-9724, 1687-9732 |
| Online-Zugang: | Volltext |
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