The invention discloses an image computer-aided diagnosis method for multi-sequence nuclear magnetic resonance images, belongs to the field of computer-aided diagnosis, and relates to a computer-aided diagnosis method for multi-sequence image processing, texture feature extraction, classification and decision fusion of magnetic resonance imaging (MRI)-based T1WI, T2WI, an arterial phase, a portal vein phase and an equilibrium phase. According to the method, five sequences of the T1WI, the T2WI, the arterial phase, the portal vein phase and the equilibrium phase of MRI are integrated under a digital image processing and mode identification framework, and the image computer-aided diagnosis is completed by means of a neural network, a voting mechanism and a decision-making tree according to three levels of region of interest (ROI) processing, multi-sequence MRI classification and individual classification. By the method, multi-parameter, multi-sequence and multidirectional imaging is provided, and a combined classifier can select a sequence having the optimal distinguishing performance from the five sequences according to different stages of an anomaly structure to serve as the classification attribute of the corresponding stage. The image computer-aided diagnosis method has the advantages of rich information, clear levels and high classification accuracy.