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Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI
OBJECTIVES: To develop an automatic method for identification and segmentation of clinically significant prostate cancer in low-risk patients and to evaluate the performance in a routine clinical setting. METHODS: A consecutive cohort (n = 292) from a prospective database of low-risk patients eligib...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599141/ https://www.ncbi.nlm.nih.gov/pubmed/32594208 http://dx.doi.org/10.1007/s00330-020-07008-z |