Biparametric prostate mri: impact of a deep learning-based software and of quantitative adc values on the inter-reader agreement of experienced and inexperienced readers

HIGHLIGHTS

  • who: Stefano Cipollari from the Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale Regina Elena, Rome, Italy have published the article: Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers, in the Journal: (JOURNAL)
  • what: The aim of this study was to evaluate the use of qADC measurements and an AI-based CE-approved software (Quantib Prostate) in the interpretation of prostate bpMRI, with focus on inter-reader agreement, performance in detecting PCa, and . . .

     

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