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Publicaties

Development and Validation of a Deep Learning Model Based on MRI and Clinical Characteristics to Predict Risk of Prostate Cancer Progression

Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study.

Patient perspectives on the use of artificial intelligence in prostate cancer diagnosis on MRI

The scientific evidence of commercial AI products for MRI acceleration: a systematic review

A framework to integrate artificial intelligence training into radiology residency programs: preparing the future radiologist

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics

Deformable MRI Sequence Registration for AI-Based Prostate Cancer Diagnosis

Does FDG-PET/CT for incidentally found pulmonary lesions lead to a cascade of more incidental findings?

Federated learning for prostate cancer detection in biparametric MRI: optimization of rounds, epochs, and aggregation strategy

Pers/media

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Pilot 'AI in radiology training' resounding success

Consortium ROBUST receives NWO funding for research into reliable AI

1,9 miljoen euro subsidie voor terugdringen van scantijd MRI bij prostaatkanker

Subsidie voor onderzoek naar snellere MRI-scan met AI

1,9 miljoen euro subsidie voor snellere MRI-scan met artificial intelligence

Subsidie voor onderzoek naar het verkorten van de duur van MRI-scans

Bijna 2 miljoen euro subsidie voor snellere MRI-scan met artificial intelligence

RUG-onderzoeker wil MRI-scan bij prostaatkanker terugbrengen naar kwartier