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Approaches to the diagnosis and treatment of prostate cancer rely on a combination of magnetic resonance imaging (MRI) and histological data. The purpose of this review is to introduce the reader to the basics of the current diagnostic approach to prostate cancer with a focus on texture analysis (TA). Texture analysis allows the evaluation of relationships between image pixels using mathematical methods, which provides additional information. First-order texture analysis of features can havedoi:10.17816/dd70170 fatcat:kosp45almfdqnadqrkq2awivay