Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis.
Purpose: To evaluate if machine learning (ML) of radiomic features extracted from apparent diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) diagnosis in Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 category 3 lesions. Methods: This multi-ins...
| Publicado en: | Abdominal Radiology Vol. 46; no. 12; pp. 5647 - 5659 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2021
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| Acceso en línea: | Ver este registro en EBSCOhost |