CSM assistant analysis system and method based on tensor image

Abstract

The invention belongs to the field of medical image assistant analysis technologies, and particularly relates to the CSM assistant analysis system and the CSM assistant analysis method based on tensor images. The CSM assistant analysis system comprises an image pre-processing module, an expert knowledge base module, an ELM learning module, a classifier module and a result output module, wherein the image pre-processing module is used for acquisition of diffusion tensor images, dual measurement registration of the diffusion tensor images, segmentation of the diffusion tensor images, and dimensionality reduction and feature extraction of the diffusion tensor images; the ELM learning module is used for utilizing an ELM learning algorithm for analyzing and solving information in an expert knowledge base; and the classifier module is used for classifying feature information extracted by the image pre-processing module according to parameters determined by the ELM learning module. The CSM assistant analysis system and the CSM assistant analysis method based on the tensor images fully excavate original information of the images, increases pattern classification precision, ensure image segmentation effect, avoid time-consuming iteration process, significantly reduce training time, and can better adapt to efficiency requirement of mass data.

Description

technical field [0001] The invention belongs to the technical field of medical image aided diagnosis, and in particular relates to a CSM auxiliary analysis system and method based on tensor images. Background technique [0002] Diffusion Tensor Imaging (DTI) technology is the only noninvasive in vivo imaging method of white matter nerve fiber tracts, and it is a special form of magnetic resonance imaging (MRI). Unlike MRI, which tracks hydrogen atoms in water molecules, diffusion tensor imaging maps the direction in which water molecules are moving. Diffusion tensor imaging maps can reveal how brain tumors affect nerve cell connections, guiding medical staff in brain surgery. It can also reveal subtle abnormal changes in the brain and spinal cord associated with stroke, multiple sclerosis, schizophrenia, dyslexia and more. Diffusion tensor imaging data is essentially a second-order tensor structure, and each voxel of it contains the three-dimensional spatial information of...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a tensor image-based CSM auxiliary analysis system and method, aiming to solve the problem that the existing vector pattern learning algorithm cannot make full use of the structural space information of the diffuse tensor image data, and the tensor data is vectorized In the process, the structure of the original data will be destroyed, the inherent correlation of the data will be lost, and the iterative process is time-consuming, which greatly increases the technical problem of training time

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