A CSM auxiliary analysis system and method based on tensor images

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 assisted diagnosis, and in particular relates to a CSM assisted analysis system and method based on tensor images. Background technique

[0002] Diffusion Tensor Imaging (DTI) technology is the only non-invasive in vivo imaging method of white matter nerve fiber bundles, and it is a special form of magnetic resonance imaging (MRI). Unlike nuclear magnetic resonance imaging, which tracks hydrogen atoms in water molecules, diffusion tensor imaging is based on the direction in which water molecules move. Diffusion tensor imaging can reveal how brain tumors affect nerve cell connections and guide medical staff to perform brain surgery. It can also reveal subtle abnormal changes in the brain and spinal cord related to stroke, multiple sclerosis, schizophrenia, and dyslexia. The diffusion tensor imaging data is essentially a second-order tensor structure, and each voxel of it contains the three-dimen...

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