AI-based automated evaluation of image quality and protocol tailoring in patients undergoing MRI for suspected prostate cancer.

Journal: European journal of radiology

PMID: 38925042

Abstract

PURPOSE: To develop and validate an artificial intelligence (AI) application in a clinical setting to decide whether dynamic contrast-enhanced (DCE) sequences are necessary in multiparametric prostate MRI.

Authors

Jonas Kluckert

Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland. Electronic address: jonas.kluckert@usz.ch.
Andreas M Hötker

Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland.
Raffaele Da Mutten

Machine Intelligence in Clinical Neuroscience (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
Ender Konukoglu
Olivio F Donati

Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland; Radiology Octorad / Hirslanden, Witellikerstrasse 40, 8032 Zurich, Switzerland.

Keywords

Aged Artificial Intelligence Contrast Media Humans Image Enhancement Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Male Middle Aged Mobile Applications Prostatic Neoplasms Reproducibility of Results Sensitivity and Specificity

External Resources

View on PubMed Access via DOI PubMed (38925042)

AI-based automated evaluation of image quality and protocol tailoring in patients undergoing MRI for suspected prostate cancer.

Abstract

Authors

Keywords

External Resources

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