Towards bridging the synthetic-to-real gap in quantitative photoacoustic tomography via unsupervised domain adaptation
The difficulty of obtaining absorption coefficient annotations hinders the practical application of deep learning in quantitative photoacoustic tomography. While training on synthetic data is easy to implement, the synthetic-to-real domain gap poses a significant challenge to model generalization. T...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | Photoacoustics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221359792500059X |
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