Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2

2019/09/01 by Baris Turkbey, Andrew B. Rosenkrantz, Masoom A. Haider +11 · 8 citations

paper · doi:10.1016/j.eururo.2019.02.033

Cited by

• Ultra-Strong Gradient Diffusion MRI with Self-Supervised Learning for Prostate Cancer Characterization
• Cancer-Net PCa-MultiSeg: Multimodal Enhancement of Prostate Cancer Lesion Segmentation Using Synthetic Correlated Diffusion Imaging
• Context-aware deep learning using individualized prior information reduces false positives in disease risk prediction and longitudinal health assessment
• RADS ALPHABET: news and tips for young and general radiologists
• In prostate cancer diagnosis, a deep learning model shows increased susceptibility to MRI quality variations compared to radiologists
• Impact of Clinical Image Quality on Efficient Foundation Model Finetuning
• Policy to Assist Iteratively Local Segmentation: Optimising Modality and Location Selection for Prostate Cancer Localisation
• Scaling Artificial Intelligence for Prostate Cancer Detection on MRI towards Organized Screening and Primary Diagnosis in a Global, Multiethnic Population (Study Protocol)