Elastic registration method of stereo MRI brain image based on machine learning

A nuclear magnetic resonance and elastic registration technology, which is applied in the fields of sensors, medical science, vaccination and ovulation diagnosis, etc., can solve the problems of difficult to distinguish attribute vectors and slow changes in image grayscale, and achieve improved registration results, improved registration accuracy, The effect of increased accuracy
CN1883386AInactive Publication Date: 2006-12-27SHANGHAI JIAO TONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANGHAI JIAO TONG UNIV
Publication Date
2006-12-27
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention relates to a method for elastic registration of stereo NMR brain images based on machine learning. The machine learning method is used to obtain the best dimension of the computation attribute vector on each point in the reference image, from which the obtained best attribute vector keeps discrepancy of the greatest extent from the attribute vector on each point around, and conformability of the greatest extent with the attribute vector on the corresponding point of the training sample. Based on the significance and consistency condition of the attribute vector on each point of the image, a standard for evaluating a key point is defined. The key point is selected automatically and hierarchically in each registration stage via the machine learning method, thus preventing the registration process from trapping in a local minimum value point. Finally, the machine learning based frame is combined with the existing registration arithmetic to complete the elastic registration of stereo NMR brain images. The invention can enhance precision and robustness of registration of both real MR images and simulated MR images, thereby establishing a foundation for the feasibility and accuracy of subsequent clinical applications.
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Description

technical field

[0001] The invention relates to a machine learning-based elastic registration method for stereoscopic nuclear magnetic resonance brain images. With the help of machine learning methods, an optimal attribute vector is learned on each point of the stereoscopic brain image to accurately represent the characteristics of the point. And the key points in the image are selected hierarchically, so as to improve the accuracy and robustness of elastic registration. The present invention can lay the foundation for subsequent clinical applications such as image fusion, precise locating of lesions, formulation of surgical plans, and curative effect tracking, and involves fields such as image elastic registration, machine learning, and stereoscopic nuclear magnetic resonance brain (MR) images. Background technique

[0002] Medical image registration has very important clinical application value. The registration of medical images obtained by using various or the same imag...

Claims

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