Super-resolution identification method of medical CT images

Abstract

The present invention discloses a super-resolution identification method of medical CT images. The method comprises the steps of creating a training set in advance to obtain a high resolution dictionary, a low resolution dictionary and an optimization dictionary, and establishing a local characteristic base of a plurality of classification target images; obtaining a to-be-processed first CT image; carrying out the up-sampling on the first CT image, and obtaining a first low resolution image corresponding to the first CT image; extracting a low resolution characteristic of the first low resolution image, and calculating a sparse coefficient of the low resolution characteristic under a dual sparse model; according to the low resolution characteristic, the sparse coefficient and the high resolution dictionary, recovering a corresponding high resolution characteristic; according to the high resolution characteristic and the first low resolution image, obtaining a corresponding first high resolution image; carrying out the pathological local characteristic comparison on the local characteristic of the first high resolution image and the local characteristics of the classification target images, and outputting a comparison result. According to the super-resolution identification method of the medical CT images, the personnel not having the professional medical knowledge can know the pathological information in the CT images.

Description

technical field [0001] The invention relates to the technical field of medical equipment, in particular to a method for super-resolution recognition of medical CT images. Background technique [0002] With the development of science and technology, modern medicine has also made great progress. In order to accurately understand the patient's condition, some modern medical instruments are often used to examine the patient. [0003] When a doctor understands a patient's condition, he often needs to use some imaging examination devices to examine the patient's body, such as obtaining X-ray images, ultrasonic images, and MRI images of the patient. However, currently these imaging devices and existing imaging technologies are limited by existing technologies, and usually cannot obtain clear images that meet high requirements. In particular, patients themselves usually do not have deep medical knowledge. When they get the various films they took in the hospital, they often cannot ...

AI Technical Summary

Problems solved by technology

However, currently these imaging devices and existing imaging technologies are limited by existing technologies, and usually cannot obtain clear images that meet high requirements

In particular, patients themselves usually do not have deep medical knowledge. When they get the various films they took in the hospital, they often cannot know the specific information of the images in the films. Recognition is even more valuable

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