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Unsupervised anomaly detection for posteroanterior chest X-rays using multiresolution patch-based self-supervised learning
The demand for anomaly detection, which involves the identification of abnormal samples, has continued to increase in various domains. In particular, with increases in the data volume of medical imaging, the demand for automated screening systems has also risen. Consequently, in actual clinical prac...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975177/ https://www.ncbi.nlm.nih.gov/pubmed/36854967 http://dx.doi.org/10.1038/s41598-023-30589-w |