Method and device for generating focus on CT image and storage medium

Abstract

The invention provides a method and device for generating a focus on a CT image and a storage medium. The method comprises the following steps: acquiring continuous original CT images and focus generation data; establishing a first-stage cube taking the focus as the center; generating a focus contour mask based on the cut CT image, the focus generation data and a pre-trained first generative adversarial network; generating a focus CT image based on the cut CT image, the focus generation data, the focus contour mask and a pre-trained second generative adversarial network; and inserting the focus CT image into an original CT image to generate a complete CT image. According to the invention, through the two generative adversarial network models, the lesion contour is generated firstly, then the complete lesion is generated, and the problems of overfitting and obvious square edges existing in other lesion generation methods are solved.

Description

technical field [0001] The present invention relates to the field of image data generation and its learning field, in particular, to a method, device and storage medium for generating lesions on CT images. Background technique [0002] X-ray computed tomography (Computed Tomography, CT) technology has been widely used in medical diagnosis, and is one of the indispensable medical imaging technologies for clinical diagnosis today. The use of artificial intelligence-based methods to assist clinical diagnosis requires a large number of CT images of lesions and normal CT images for controlled trials. On the one hand, in the actual image acquisition process, there are relatively few images with lesions. Secondly, manual labeling is expensive. On the other hand, the acquisition of a large number of medical images will seriously violate the privacy rights of patients. [0003] The current lesion generation method is to use a rectangle on the image to block the position where the ...

AI Technical Summary

Problems solved by technology

The problem with this operation is that there are obvious rectangular edges around the generated lesions, or a strong overfitting effect

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