The present invention provides a YOLO convolutional neural network-based cholelithiasis CT medical image data enhancement method, comprising: constructing a medical image data enhancement convolutional neural network, the network consisting of four convolution units; first, constructing a medical image data set as an input to the neural network, and performing operations such as enhancing edge information and removing redundant information on an image; then, segmenting the image according to a segmentation threshold to form multiple image blocks; and expanding the data set by scaling, rotating, and translating, etc.. The convolutional neural network is continuously trained using the data set; functions of the network on the image, such as feature extraction, contrast stretching, histogram equalization, and image reconstruction, are self-adaptively enhanced; a convolutional neural network model for medical image data enhancement is generated. By means of the method, the medical image data enhancement function can be completed in real time, and a good visual effect and medical effect can be obtained.
YOLO CONVOLUTIONAL NEURAL NETWORK-BASED CHOLELITHIASIS CT MEDICAL IMAGE DATA ENHANCEMENT METHOD