The invention provides a prostate image segmentation method. The method comprises the steps that S1, prostate region training samples are acquired and marked; S2, a training prostate region is preprocessed to obtain a preprocessing result; S3, a full-convolution network structure for prostate region-of-interest segmentation is constructed; S4, the training samples are utilized to train a prostatesegmentation model so as to acquire an optimal prostate image segmentation model; S5, a prostate region sample of an object is acquired and marked; S6, a testing prostate region is preprocessed to obtain a preprocessing result; S7, the trained segmentation model is used to segment a test set; S8, segmentation results of the full-convolution network are post-processed; and S9, evaluation indexes for image segmentation are selected to perform statistical evaluation on the segmentation results. Through the method, pixel classification precision is improved, and the method has scale invariance, ishigh in segmentation speed and has a good application prospect.