1. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a computer cause the computer to perform a method associated with detecting prostate cancer (CaP) in a magnetic resonance (MR) image of a prostate of a CaP patient, the method comprising: accessing a digitized MR image of the prostate, where the digitized MR image comprises a set of pixels and gray-level intensity information about the pixels; labelling one or more pixels in the digitized MR image as positive pixels; labelling one or more pixels in the digitized MR image as negative pixels; extracting a local binary pattern (LBP) for a first pixel in the one or more positive pixels at a plurality of scales; extracting an LBP of a second pixel in the one or more negative pixels at the plurality of scales; calculating a first Hamming distance for the one or more positive pixels and the one or more negative pixels at the plurality of scales; learning a vector, where the vector weighs the first Hamming distance at the plurality of scales; generating a template LBP by extracting an LBP from a template pixel in a non-empty subset of the set of pixels; calculating second Hamming distances of the template LBP and of the LBP of a pixel other than the template pixel in the set of pixels at the plurality of scales; calculating a weighted sum of the second Hamming distances at the plurality of scales as a function of the second Hamming distances and the vector; generating a statistical probability heatmap based, at least in part, on the weighted sum, where co-ordinates of the heatmap with higher probability indicate a higher probability that a region of the prostate corresponding to the co-ordinate is cancerous, and displaying the statistical probability heatmap to distinguish between cancerous and benign tissue on a per-pixel basis.