Multiparametric MRI (MP-MRI) has been widely used for detection of Prostate Cancer (PCa). In this study, we propose a new method using MP-MRI including T2-weighted (T2W) and dynamic contrast enhanced (DCE-) MRI for detection of PCa. 32 patients who had high prostate specific antigen (PSA) level recruited. We generated predictive models by extracting radiomics features and classifying benign and malignant lesions. The feature scores are evaluated with Relieff feature selection for each of the modalities. The fused classifier using decision template method showed the highest performance with accuracy, specificity, and sensitivity of 100.
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