Objective image quality evaluation method for optimizing medical image reconstruction parameter

Abstract

The invention discloses an objective image quality evaluation method for optimizing medical image reconstruction parameters. The objective image quality evaluation method comprises the steps of: 1, constructing a plurality of virtual reference images by adopting a circular topping method, wherein quality of a reconstructed image can be analyzed by utilizing a full-reference image quality evaluation algorithm, and parallel processing can be achieved; 2, analyzing self-similarities of the images from different scales and different directions by utilizing Daubechies wavelet transform combined with eigenvalue decomposition; 3, and regarding the obtained self-similarities of the reconstructed images as quality factors, and carrying out bubble sorting on the quality factors to obtain quality levels of the reconstructed images, wherein the highest quality level corresponds to the optimal reconstruction parameter. The objective image quality evaluation method offers image quality objective evaluation which has good consistency with the subjective evaluation, and particularly can accelerate optimizing process of parameters in a medical image reconstruction algorithm.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, in particular to an objective image quality evaluation method for optimizing medical image reconstruction parameters. Background technique [0002] Medical image quality evaluation has long been used by doctors to evaluate the performance of X-ray, computed tomography, magnetic resonance imaging, ultrasound imaging and many other modal imaging equipment. This evaluation is usually subjective and is called subjective image quality evaluation. In addition, a single imaging modality also has different reconstruction algorithms, and the quality of reconstruction also needs to be evaluated subjectively by doctors, which is time-consuming and laborious in the process of optimizing complex reconstruction parameters. In these application scenarios, objective image quality evaluation based on artificial intelligence and machine learning highlights its advantages due to its fast calculati...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the invention is to solve the quality level calibration problem of a series of reconstructed images with the same semantics

Provide an objective image quality evaluation method for optimizing medical image reconstruction parameters

The invention is based on the human visual system, making full use of the self-similarity of images with the same semantics, and extracting self-similar information. In order to solve the quality level calibration problem of a series of reconstructed images in the specific operation process, a loop top strategy is adopted combined with the quality factor The sorting method is used to obtain the quality level of a series of images, and a good image quality evaluation effect has been achieved.

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