Diffusion MRI microstructure imaging-based minimum nuclear error analysis method

Abstract

The invention discloses a diffusion MRI microstructure imaging-based minimum nuclear error analysis method. The method comprises the following steps of: (1) establishing a diffusion organization model, wherein a microstructure model comprises three features of a microstructure: linear structure anisotropy (LSA, D1), planar structure anisotropy (PSA, Dp) and spherical structure isotropy (SSI, Ds), and each feature model in each voxel is described as a mixed anisotropy / isotropy model; (2) calculating feature scalars, wherein the quantities of blocked and limited diffusions are captured through calculating differences between estimated microstructure scales; (3) generally presenting the minimum nuclear error analysis method; and (4) carrying out algorithm optimization, importing an auxiliary matrix variable Z, realizing a formula (as shown in the specification) and solving the minimum problem by utilizing an enhanced Lagrange multiplier. By combining a diffusion tensor imaging technology, the diffusion MRI microstructure imaging-based minimum nuclear error analysis method provided by the invention is capable of stably and efficiently estimating the fiber structures of relatively small intersection angles.

Description

technical field [0001] The invention relates to the fields of medical imaging and neuroanatomy under computer graphics, in particular to a minimum kernel error analysis method based on diffusion MRI microstructure imaging. Background technique [0002] With the development of the times and the advancement of medical imaging technology, diffusion tensor imaging technology has become more and more influential in neuroscience research. Advanced neuroimaging technology is indispensable in this era; diffusion tensor imaging Technology is an emerging method to describe the structure of the brain; at present, diffusion tensor imaging technology is being widely used in psychiatric diseases and auxiliary means of diagnosis, and can even be used in the formulation of preoperative surgical plans. Contributions in the medical field have irreplaceable advantages; therefore, research on diffusion tensor imaging technology is of great significance to brain science. [0003] Diffusion tens...

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Problems solved by technology

[0004] In order to overcome the shortcomings of the prior art that cannot stably and efficiently estimate the fiber structure of smaller intersection angles, the present invention combines diffusion tensor imaging technology to provide a diffusion-based MRI microstructure that can stably and efficiently estimate the fiber structure of smaller intersection angles A Minimal Kernel Error Analysis Method for Imaging

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