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Image processing method used for brain MRI image classification

An image processing and image technology, which is applied in the field of image processing, can solve the problems of increasing the instability of the result and increasing the amount of calculation of the traversal method, etc.

Active Publication Date: 2016-06-22
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology

[0004] Template-based algorithms often make the results affected by the template space selection and establishment, which increases the instability of the results
The traversal algorithm can greatly improve the utilization of image information

Method used

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  • Image processing method used for brain MRI image classification
  • Image processing method used for brain MRI image classification
  • Image processing method used for brain MRI image classification

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Embodiment approach

[0075] A kind of embodiment, set the MR image of the individual of a group of known classification results as I={N 1 ,N 2 ,...,N m ,A 1 ,A 2 ,...,A n}, where {N 1 ,N 2 ,...,N m} is the first type of MRI image set, which is an image of a normal population, such as an image of an elderly population; {A 1 ,A 2 ,...,A n} is the second type of MRI image set, which can be a population image of a certain disease, such as a high-risk individual or patient of Alzheimer's disease. The MR image of the individual to be classified is defined as M.

[0076] Step 104: Extract similarity information between the first type of MRI image set and the second type of MRI image set.

[0077] An embodiment, for I={N 1 ,N 2 ,...,N m ,A 1 ,A 2 ,...,A n} Each image in the data set is corrected for position and offset field. Randomly select p first-type MRI image set individuals and q second-type MRI image set individuals (p+q1 ,N 2 ,...,N p ,A 1 ,A 2 ,...,A q}={I 1 , I 2 ,...,I ...

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Abstract

The invention discloses an image processing method used for brain MRI image classification. The Image processing method includes the steps of: obtaining a first-type MRI image set and a second-type MRI image set; extracting similarity information of the first-type MRI image set and the second-type MRI image set; using a Nystrom algorithm and a projection algorithm to calculate Euclid coordinates of individuals in the first-type MRI image set and the second-type MRI image set; using the similarity information and the Euclid coordinates to perform classification training on the first-type MRI image set and the second-type MRI image set, thereby obtaining a judgment criterion; extracting image features of an MRI image set to be classified, and performing image classification according to the judgment criterion. The invention also discloses a device based on the abovementioned method. The image processing method used for brain MRI image classification adopts the Nystron algorithm to approximate a similarity matrix, thereby greatly reducing the calculated amount.

Description

technical field [0001] The present application relates to the field of image processing, in particular to an image processing method for brain MRI image classification. Background technique [0002] Brain MRI image classification adopts a template-based image processing method: (1) based on voxel grayscale; (2) based on cerebral cortex thickness; (3) based on specific regions of interest. The above methods all use the template (or standard) space, so this kind of method is called template-based algorithm. [0003] In the prior art, a pairwise ergodic comparison method of registration deformation field quantification is also used. In the feature acquisition, the deformation field registered between images is used and quantified to describe the difference in anatomical structure; the individual images are compared in pairs, and the feature obtained by this traversal method is not a one-dimensional vector, but a multi-dimensional vector. The multi-dimensional vector is quanti...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2413
Inventor 隆晓菁张丽娟姜春香刘新郑海荣
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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