Fetal craniocerebral section image anomaly judgment and analysis method and device

The invention relates to an anomaly judgment and analysis method and device for a fetal craniocerebral section image. The method comprises steps of acquiring a craniocerebral section image data set; preprocessing the craniocerebral section image data set to obtain each preprocessed section image; inputting the preprocessed section images into an automatic encoder determined through training to obtain image features of the preprocessed section images; and inputting the image features of the preprocessed section image into a classifier determined through training to obtain a qualitative classification result of the craniocerebral section image data set. According to the method, the classifier determined by training is used for classifying the craniocerebral section image data set to obtain the qualitative classification result of the craniocerebral section image data set, so labor cost and the time cost can be effectively reduced, and accuracy and repeatability of an analysis result canbe obviously improved whi