Motion correction method for magnetic resonance multiple excitation diffusion imaging

Abstract

The invention discloses a motion correction method for magnetic resonance multiple excitation diffusion imaging. The method comprises the steps of collecting a magnetic resonance multiple excitation sequence; obtaining an image echo signal and a two-dimensional navigation signal through a magnetic resonance scanning sequence; estimating motion parameters through the two-dimensional navigation signal; performing rotational and translational correction on the image echo signal and the two-dimensional navigation signal according to the motion parameters, and discarding tainted data, thereby obtaining corrected data; integrating the corrected data collected in multiple excitation to perform parallel imaging reconstruction; estimating rotational motion parameters through an image registration algorithm to perform diffusion gradient correction on a reconstructed image; and performing final calculation by utilizing corrected diffusion image and diffusion gradient to obtain diffusion tensor imaging parameters. According to the method, various motion errors in a magnetic resonance diffusion imaging scanning process can be effectively corrected, so that an artifact-free high-resolution diffusion tensor image is obtained, the errors are effectively reduced, and the accuracy of calculating magnetic resonance diffusion imaging tensor parameters is improved.

Description

technical field [0001] The invention relates to the technical field of magnetic resonance diffusion imaging, in particular to a motion correction method for magnetic resonance multiple excitation diffusion imaging. Background technique [0002] Magnetic resonance diffusion weighted imaging can non-invasively detect the microscopic Brownian motion of water molecules in the human body, and provide information on microstructure and tissue function. It is an important neuroimaging technique and is widely used in clinical and research. [0003] Since diffusion imaging, especially high-resolution diffusion tensor imaging requires a long scanning time, the patient's involuntary movement is a problem that must be solved in clinical use. Methods such as immobilizing the patient's head not only make the patient uncomfortable, but also cannot completely prevent movement. Therefore, motion correction technology is a difficult point and a hotspot in high-resolution diffusion imaging of ...

AI Technical Summary

Problems solved by technology

The motion amplitude of the second kind of motion is smaller than the pixel size of the image, so it will not cause the overall position change, but if this kind of motion occurs when the diffusion gradient is applied, it will cause a sharp phase change of the image, resulting in the phase difference between different excitation data. Aliasing artifacts due to differences, so this type of motion must be corrected

The third type of motion is relatively large-scale motion. This type of motion can be defined as the position change between different excitations and acquisitions. If this type of motion occurs during gradient application, the acquired signal will be destroyed and the image will be difficult to recover. , if it occurs in other acquisition stages, the position difference between different excitations will lead to errors when integrating and reconstructing the data collected by different excitations, making it difficult to obtain an ideal image, resulting in problems such as blurring of the final diffusion image

[0004] Due to the existence of the second and third types of motion errors, the single-shot echo-planar technique is still the most widely used clinically, and the development of high-resolution diffusion imaging is limited.

High-resolution diffusion imaging with multiple shots faces three main motion-induced errors: (1) phase error due to small intra-pixel motion, which can cause severe aliasing artifacts; (2) The overall movement of the image caused by large movements produces blurred artifacts in the final image; (3) The direction of the diffusion gradient changes relative to the original coordinate system due to the rotational movement of the head, thus affecting the calculation of the final diffusion parameters

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