The present invention relates to the technical field of image processing, and specifically discloses an auxiliary system for predicting the range of early cancer lesions based on deep learning, including: an image acquisition module, used to acquire sample images of digestive tract endoscopes with target frames, and perform Preprocessing, recording the coordinate information of the end point of the target frame, and generating a training image set; the model building module is used to construct a convolutional neural network model, and perform iterative training on the convolutional neural network model based on the training image set, and then perform a test, and the test is completed Finally, the successfully trained convolutional neural network model is obtained; the range division module is used to receive the image to be diagnosed of the digestive tract endoscope, judge the image to be diagnosed based on the successfully trained convolutional neural network model, and output the predicted endpoint of the image to be diagnosed Coordinate information; the range division module draws a target frame on the image to be diagnosed based on the coordinate information of the predicted endpoint. By adopting the technical scheme of the invention, the range of early cancer focus can be marked.