Parameter error estimation method and device of magnetic resonance diffusion tensor imaging

Abstract

The invention provides a parameter error estimation method and device of magnetic resonance diffusion tensor imaging. The method comprises the steps that through magnetic resonance scanning, a diffusion weighted graph is collected; the diffusion tensor of each pixel point in the diffusion weighted graph is estimated according to the diffusion weighted graph; anisotropy coefficients and average diffusion coefficients are calculated according to the diffusion tensors; an error graph of the diffusion weighted graph is calculated; the errors of the diffusion tensors are calculated according to the diffusion tensors and the error graph of the diffusion weighted graph; the errors of the diffusion tensors, the anisotropy coefficients and the average diffusion coefficients are substituted into a preset parameter error calculation model to calculate and obtain the average diffusion coefficient errors and the anisotropy coefficient errors. According to the method and device, the distribution condition of the errors in a magnetic resonance diffusion imaging parameter graph can be visually expressed, and therefore image quality estimation of diffusion tensor imaging is facilitated.

Description

technical field [0001] The invention relates to the technical field of magnetic resonance imaging, in particular to a parameter error estimation method and device for magnetic resonance diffusion tensor imaging. Background technique [0002] Magnetic resonance diffusion tensor imaging (DTI) is a special form of magnetic resonance imaging, which uses the principle of anisotropy of free thermal motion of water molecules in tissues to detect the microstructure of tissues. As a new type of non-invasive detection technology, DTI can be used for imaging of nervous system, muscle and other tissues and organs, providing important imaging data for early diagnosis of multiple sclerosis, diffuse brain injury, liver tumor, myocardial infarction and other major diseases. [0003] The diffusion tensor imaging process is as follows: First, a set of data is acquired by magnetic resonance, including a T2-weighted image (generally called a b0 image) and a diffusion-weighted image (DWI) obtain...

AI Technical Summary

Problems solved by technology

Because the traditional MRI technology does not have a parameter error estimation method for MRI, it is difficult to estimate the error distribution of the DTI parameter map

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