Projection data recovery-guided nonlocal mean low-dose CT reconstruction method

Abstract

The invention discloses a projection data recovery-guided nonlocal mean low-dose CT reconstruction method, which comprises the following steps of: (1) acquiring low-dose projection data by using CT imaging equipment; (2) converting the low-dose projection data; (3) performing traditional FBP reconstruction on the low-dose projection data acquired in the step (1); (4) filtering the converted low-dose projection data; (5) performing traditional FBP reconstruction on the low-dose projection data filtered in the step (4); (6) calculating a weight matrix for a standard dose image acquired in the step (5); and (7) performing weighted average filtering on the reconstructed low-dose image acquired in the step (3) by utilizing the weight matrix acquired in the step (6) to acquire the recovered low-dose image. In the method, low-dose radiation is achieved, and a high-quality CT reconstruction image can be acquired. The method has good robustness, and has good performance in the two aspects of noise elimination and artifact suppression.

Description

technical field [0001] The invention relates to an image reconstruction method of medical images, in particular to a non-local average low-dose CT reconstruction method guided by projection data restoration. Background technique [0002] In recent years, more and more attention has been paid to the radiation dose received by patients undergoing CT examination and the associated cancer risk. With the wide application of multi-slice CT and dual-source CT in clinical practice, the use of new CT equipment has resulted in greater X-ray doses, making people more and more concerned about the potential harm of CT doses to the human body and how to ensure image quality. The X-ray dose is minimized under the premise of quality. [0003] The traditional radiation dose reduction methods mainly include reducing the X-ray tube voltage, tube current, and shortening the exposure time. However, the image quality reconstructed by the above method will be severely degraded, which is difficul...

AI Technical Summary

Problems solved by technology

However, due to the large amount of CT projection data and the time-consuming iterative calculation, it is difficult to meet the requirements of real-time interaction in clinical practice, and its methods are mostly limited to theoretical discussions

In addition, post-processing methods that directly filter low-dose images can only obtain information from the image itself, and its processing accuracy strongly depends on the noise and artifact characteristics of the image data.

However, the noise and artifact characteristics of low-dose images are extremely unstable and difficult to accurately describe, which also makes it difficult for most low-dose CT image filtering methods based on post-processing to obtain clinical applications.

In addition, the low-dose reconstruction method based on projection data filtering can effectively suppress the noise and artifacts in the reconstructed image, but the resolution of the reconstructed image is lower than that directly reconstructed from the unprocessed projection data. The biggest problem faced in practical application

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