Prostate cancer is one of the deadliest diseases in the world, and after skin cancer, it is the most common cancer among men. To detect prostate cancer, radiologists rely chiefly on MRI (magnetic resonance imaging) scans in order to determine the presence of cancer, its progression, and the threat it poses to the patient. With the data from these MRI scans, radiologists are able to devise individualized treatment plans for each patient, ensuring the best possible care. On the cutting edge of radiotherapy and cancer treatment, Mayo Clinic has recently installed a cyclotron for producing radioactive nucleotides (PET tracers) in addition to a PET/MRI machine capable of acquiring nuclear medicine and MRI data in a single exam. This development will greatly benefit radiologists by providing improved data sets and greater options for all cancer patients. Recently, the radiology department at Mayo Clinic has began an initiative to streamline the diagnostic and treatment process of cancer, with a focus on prostate cancer. This research involves classifying the prostate cancer MR images into two groups: screening and staging, and then analyzing it. While screening exams determine the presence of cancer, staging exams take a deeper look into the severity and progression of the cancer in order to develop a treatment plan. With the application of machine learning, image analysis, and the compilation of patient data, this research aims to create a faster, more efficient, and more effective infrastructure for radiologists to diagnose and treat prostate cancer.