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Multimodal medical image registration method fusing gradient information with generalized entropy similarity

A technology of medical image and gradient information, applied in the field of medical image processing, can solve the problems of low registration error and no consideration of image gradient, etc.

Active Publication Date: 2018-01-30
ZHONGYUAN ENGINEERING COLLEGE
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Problems solved by technology

The registration experiments of preoperative brain magnetic resonance images and intraoperative ultrasound images have confirmed that this method can obtain lower registration errors. However, this method only uses the direction information of the gradient and does not consider the image gradient model.

Method used

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  • Multimodal medical image registration method fusing gradient information with generalized entropy similarity
  • Multimodal medical image registration method fusing gradient information with generalized entropy similarity
  • Multimodal medical image registration method fusing gradient information with generalized entropy similarity

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Embodiment Construction

[0072] Such as image 3 As shown, a multimodal medical image registration method that combines gradient information and generalized entropy similarity, the steps are as follows:

[0073] S1, Construct a generalized entropy similarity measure.

[0074] S1.1, define the Arimoto entropy A α ;

[0075]

[0076] Among them, X is a discrete random variable; α is the parameter that controls the non-expandability of Arimoto entropy; M is the number of elements of the discrete random variable X; i is the element number of the probability distribution P of the discrete random variable X; p i is the i-th element of the probability distribution P.

[0077] According to L'Hopital's rule, when α→1, the limit of Arimoto entropy is equal to Shannon entropy, so Shannon entropy can be regarded as a special case of Arimoto entropy.

[0078] S1.2, construct the Jensen-Arimoto divergence (JAD).

[0079]

[0080] In the formula, A α (·) represents the Arimoto entropy, ω i represents th...

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Abstract

The invention discloses a multimodal medical image registration method fusing gradient information with generalized entropy similarity. The method comprises steps of: S1, constructing a generalized entropy similarity measure; S2, constructing the gradient measure of an image to be registered; S3, constructing the similarity measure of the image to be registered; S4, constructing a registration model of a multimodal image; and S5, solving the registration model. The method comprehensively takes account of the gradient information and the grayscale distribution characteristics of different modalmedical images, and implements the accurate registration of the multimodal medical image, constructs the generalized entropy similarity measure based on a generalized information entropy, and has a wide range of properties. Rather than taking the grayscale difference between the images into consideration, the method calculates the information theory similarity between the images to be registeredby using the joint probability distribution of the grayscale values of the two images, is not only applicable to the same-modal medical images but also to the different-modal medical images with largegrayscale difference, and is expanded in the use range.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and in particular relates to a multimodal medical image registration method which combines gradient information and generalized entropy similarity. Background technique [0002] Medical image registration is an important technology in the field of medical image processing, which plays an important role in medical information fusion, tumor growth monitoring, image-guided surgical treatment, and radiotherapy planning. The rapid development and wide application of microelectronics, computers, and information science have led to the rapid development of medical imaging technology. With the continuous development of imaging equipment, the amount of information obtained by doctors from medical images has increased dramatically. The image information acquired by a single imaging device can no longer meet the needs of some specific applications, and the previous image processing methods...

Claims

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Application Information

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IPC IPC(8): G06T7/30G06T7/00
Inventor 李碧草刘洲峰王贝张爱华黄杰舒华忠
Owner ZHONGYUAN ENGINEERING COLLEGE