The classification of medical images is a research hotspot in the field of computer-aided diagnosis and pattern recognition. Accurately categorizing human anatomical structure and lesion areas can maximally assist doctors in diagnosing diseases more accurately and quickly. Herein, for the particularity of medical images, typical medical image classification is first summarized and then described according to four aspects: image preprocessing, image segmentation, feature extraction, and classification. Next, the application of deep learning theory to medical image classification is introduced and discussed. Finally, the shortage of the existing medical image classification methods is addressed, and the development trend of the latest theories of deep learning in the field of medical image classification is discussed.