Computer-aided diagnosis (CAD) for prostate cancer (PCa) detection based on multiparametric MRI (mpMRI) has become an active field of research, which has shown good stand-alone performance. Before its widely use in daily clinical work, further study still should be done for CAD reading paradigm and the interaction between CAD and human reader. In this article, we implemented CAD in the real world practice, aiming to evaluate the feasibility of integrating CAD as a second reader into the clinical diagnostic process. The results showed this reading paradigm was feasible and CAD might help readers detect more patients with PCa.
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