Abstract
The use of medical imaging, especially multiparametric magnetic resonance imaging (MRI), is critical in the diagnosis of prostate cancer. This technique enables better visualization and localization of prostate lesions, which has led to improved prostate cancer detection and classification. However, significant inter-observer variability exists in these imaging reports. AI solutions can assist radiologists during the interpretation process, particularly those with low to intermediate levels of experience. First experiences in prostate lesion detection on multiparametric MRI using deep learning have demonstrated higher detection sensitivities compared to classical machine learning algorithms. This will continue to improve in the future with the availability of larger and diverse prostate MRI datasets. More studies are needed to determine the practical value of AI in this field.
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