Related prediction model-based method for detecting structural deformation in magnetic resonance image
A technology of magnetic resonance images and nuclear magnetic resonance images, which is applied in the field of medical image processing of magnetic resonance images, can solve the problems of objectivity and lack of repeatability, and achieve the effect of precise geometric structure
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2011-09-14
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Abstract
Description
technical field
[0001] The invention relates to a method for detecting structural deformation in a magnetic resonance image based on a correlation prediction model, and belongs to the fields of magnetic resonance image medical image processing, computational neuroanatomy, and the like. Background technique
[0002] The use of magnetic resonance images as an auxiliary diagnosis of brain diseases has been a common method. The use of computer medical image processing technology for magnetic resonance images is more scientific for the identification of brain magnetic resonance images. At present, the quantification of brain structural deformation in magnetic resonance images is One of the index parameters for medical image processing.
[0003] Current methods for quantifying structural deformation of the brain due to brain atrophy in MRI images can broadly be divided into two categories. One is based on multi-time-point magnetic resonance structural images. This type of method...
Examples
Embodiment Construction
[0034] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:
[0035]Steps in this embodiment: 1) For a group of normal subjects, reconstruct the surface of the cerebral cortex according to their magnetic resonance structural images, and use the elastic deformation registration algorithm to register all the cortical surfaces to the standard template space to construct a set of training samples , and then use the training samples to calculate the structural correlation matrix between vertices on the surface of the cerebral cortex; 2) For the sample to be tested, reconstruct the surface of the cerebral cortex according to its magnetic resonance structural image; 3) On the surface of the cerebral cortex of the subject to be tested Select the area to be detected, and according to the structural correlation matrix calculated in step 1), use the typical correlation prediction model to predict the expected coordinate value of the ve...