Abstract: A SPECT imaging prediction model creation method, apparatus, device, and storage medium. The method includes: obtaining a training set including a plurality of scanning image groups, wherein each scanning image group includes a standard acquisition duration SPECT image and a short acquisition duration SPECT image that corresponding to each other; performing network construction on the basis of deep convolutional neural network to obtain a network to be trained; taking the short acquisition duration SPECT image in the training set as input-side training data, taking the standard acquisition duration SPECT image in the training set as output-side training data, training the network to be trained to obtain a SPECT imaging prediction model, so as to predict SPECT prediction image of short acquisition duration SPECT image under standard acquisition duration by using the SPECT imaging prediction model. The SPECT imaging time is significantly reduced while maintaining the imaging quality of medical images.

Abstract: Disclosed in the present invention is a method for enhancing the quality and resolution of CT images based on deep learning, comprising the following steps: S1: pre-processing collected clinical data to obtain a data set; S2: building a deep learning model comprising a generative network, a decider network, and a cognitive network; S3: building a loss function; S4: using the data set and the loss function to update the parameters of the iterative generative network in order to obtain a trained deep learning model; and S5: inputting a low-quality low-resolution image into the trained deep learning model to obtain a high-quality high-resolution image.