Method for evaluating medical image quality in combination with phase consistency, gradient magnitude and structural prominence

Abstract

The invention discloses a method for evaluating medical image quality in combination with phase consistency, gradient magnitude and structural prominence. The method comprises the following steps: 1) calculating a phase consistency map of a reference image and a distorted image by using a log-Gabor wavelet; 2) calculating a gradient magnitude map of the reference image and the distorted image by using a Scharr operator; 3) obtaining a local image quality map in combination with the phase consistency map obtained in the step 1) and the gradient magnitude map obtained in the step 2); 4) calculating a structural prominence map, based on a human eye visual feature, of the reference image; 5) performing weighting summation on the image quality map in the step 3) by using the structural prominence map as an aggregation policy to obtain an image quality score; and 6) when the image quality score is higher than a preset score threshold, judging that the medical image quality is relatively high. The method is relatively high in reliability and high in practicality.

Description

technical field [0001] The invention belongs to the field of medical image evaluation, in particular to a medical image quality evaluation method. Background technique [0002] High-quality medical images often help to improve the efficiency of doctors' diagnosis and reduce the occurrence of medical accidents, but the current research on medical image quality evaluation lags far behind that of natural image quality evaluation. This is mainly limited by the constraints of hardware equipment, the limited number of public data sources, and the professional background of medical imaging staff. At present, there is no method with high reliability, so the research on medical image quality evaluation is a necessary work. [0003] At present, the image quality evaluation method based on statistical data and the image quality evaluation method (SSIM) based on structural features are still the most used medical image quality evaluation indicators, and the image quality evaluation met...

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Problems solved by technology

[0005] In order to overcome the shortcomings of the traditional medical image quality evaluation index and human subjective evaluation results, the consistency is not too high, and the practicability is poor when evaluating t

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