The invention discloses an autism detection method, device and system based on a graph theory, and belongs to the technical field of medical image processing. The method comprises the following steps:constructing a brain function network topological graph corresponding to each magnetic resonance image by taking a threshold value with the lowest network consumption as a binarization threshold value; determining an abnormal brain region based on the difference statistical information of the node degree information of the autistic patient and the normal person, and extracting the feature information of the abnormal brain region, namely the node degree information of the node corresponding to the brain region; and performing model training and detection of an autism dichotomy classifier basedon the extracted feature information, and providing auxiliary diagnosis help for autism diagnosis. According to the autism detection system in the multi-feature fusion mode, another auxiliary diagnosis help is provided for autism diagnosis, and the autism detection recognition rate is improved to a certain extent. The detection system can also be used for automatic detection in the health fieldsof smoking addiction, network addiction, network game addiction, knowledge and the like.
Autism detection method, device and system based on magnetic resonance image