1. A method for automatic prostate segmentation in magnetic resonance (MR) image data, comprising: performing intensity normalization on an MR image of a patient; obtaining an initial prostate segmentation in the MR image by aligning a learned statistical shape model of the prostate to the MR image using marginal space learning (MSL); and refining the initial prostate segmentation using one or more trained boundary classifiers.