Deep learning with attention modules and residual transformations improves hepatocellular carcinoma (HCC) differentiation using multiphase CT
Abstract Background We hypothesize generative adversarial networks (GAN) combined with self‐attention (SA) and aggregated residual transformations (ResNeXt) perform better than conventional deep learning models in differentiating hepatocellular carcinoma (HCC). Attention modules facilitate concentra...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-03-01
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| Series: | Precision Radiation Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/pro6.70003 |
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