Robust and accurate pulmonary nodule detection with self-supervised feature learning on domain adaptation
Medical imaging data annotation is expensive and time-consuming. Supervised deep learning approaches may encounter overfitting if trained with limited medical data, and further affect the robustness of computer-aided diagnosis (CAD) on CT scans collected by various scanner vendors. Additionally, the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Radiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fradi.2022.1041518/full |