Liver pathological image sample enhancement method based on random transformation

The invention relates to a liver pathological image sample enhancement method based on random transformation, which comprises the following steps: 1) carrying out block division on a liver pathological image to obtain a plurality of image small blocks; 2) performing random transformation on each image small block to form an extended sample; wherein the random transformation comprises more than one of horizontal mirror image overturning, vertical mirror image overturning, cutting, brightness adjustment, saturation adjustment and hue adjustment; and 3) inputting the extended sample into a deep learning model to train the liver pathological image, and performing corresponding enhancement on the liver pathological image to obtain an enhanced sample of the liver pathological image. According to the method, original pathological samples can be effectively expanded, the problems of insufficient sample number and non-uniform sample distribution are solved to a certain extent, the requirement of a large sample size of