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Bidirectional meta-Kronecker factored optimizer and Hausdorff distance loss for few-shot medical image segmentation
To increase the accuracy of medical image analysis using supervised learning-based AI technology, a large amount of accurately labeled training data is required. However, the supervised learning approach may not be applicable to real-world medical imaging due to the lack of labeled data, the privacy...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199045/ https://www.ncbi.nlm.nih.gov/pubmed/37208448 http://dx.doi.org/10.1038/s41598-023-35276-4 |