DTI image analytical method based on multiple variables

Abstract

The invention discloses a DTI image analytical method based on multiple variables. The DTI image analytical method based on the multiple variables is used for determining and extracting diseased areas of the brain white matter in the disease brain mechanism research, thereby providing an imaging basis for clinical treatment. The method includes the specific steps that data are preprocessed, wherein the preprocessing procedures include eddy current removal, head motion correction, cranium removal, dispersing and fitting and white matter skeleton building; characteristic extraction is conducted on the preprocessed data, the significant difference areas of a patient group and a healthy people group are obtained through replacement inspection and with the ages serving as the concomitant variables, the average value of the certain variables in the significant difference areas is worked out respectively, and the characteristic value is obtained; cross validation is conducted through a leave-one-out method, whether the stop criterion is met or not is judged, and if not, the average weight value of each characteristic is worked out, and the characteristic with the minimum average weight value is removed until the stop criterion is met; the finally obtained brain area is the brain lesion area. According to the method, the DTI imaging mode is adopted, the imaging basis is provided for finding the lesion area in the clinical treatment through the multivariable research method.

Description

technical field [0001] The invention relates to an image analysis method, in particular to a multivariate-based DTI image analysis method. Background technique [0002] Diffusion tensor imaging (DTI) is a non-invasive imaging technique that can provide the diffusion movement of water molecules in vivo. It can detect microscopic changes in tissues that cannot be observed by traditional MRI. It is a major breakthrough in MR imaging technology. Pattern classification based on brain imaging information is a hot topic in current brain imaging research. It is an important application of computer-aided analysis to calculate the possibility of a DTI image having a certain attribute by using the image classification method, or to automatically distinguish the category attribute of the image. [0003] "Alexander AL, Lee JE, et al. Diffusion tensor imaging of the corpus callosum in Autism. Neuroimage. 2007; 34(1):61–73." Using a region-of-interest-based approach to study the role of t...

AI Technical Summary

Problems solved by technology

However, this atlas-based method cannot extract the relevant variables of the sub-regions under the atlas as features, so that it is impossible to find the lesioned regions in the sub-regions

At the same time, this method does not consider the influence of age on white matter

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