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A Feature-Level Medical Image Fusion Method Based on 3D Shearlet Transform

A technology of medical image and fusion method, which is applied in the field of medical image processing and application, and can solve problems such as low quality of sparse representation ability fusion image, adverse effects of medical diagnosis, and easy to ignore information, etc.

Active Publication Date: 2017-05-10
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0007] In view of the above-mentioned prior art, the purpose of the present invention is to provide a feature-level medical image fusion method based on 3D shearlet transform, which solves the problem of the fusion method based on wavelet transform and pyramid transform. The quality of the fused image is relatively low due to the representation ability; as well as the defect that locally important but insignificant information is easily ignored during image fusion, and these defects will eventually have an adverse effect on medical diagnosis

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  • A Feature-Level Medical Image Fusion Method Based on 3D Shearlet Transform
  • A Feature-Level Medical Image Fusion Method Based on 3D Shearlet Transform
  • A Feature-Level Medical Image Fusion Method Based on 3D Shearlet Transform

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[0067] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0068] Taking T2* magnitude image and QSM image as an example, this experiment uses the method of the present invention to process the three-dimensional T2* magnitude image and QSM image, and finally obtains a fusion image. In the example, the size of the image is 128×128×128.

[0069] The image fusion method of this embodiment first considers how to represent the anisotropy of the three-dimensional image, and the shear transform can well represent the anisotropic characteristics of the image; secondly, considering the influence of the translational change properties brought about by the DWT transform, a dual-tree complex wavelet transform is performed DTCWT; Finally, it is considered to fuse as much information as possible into the fusion coefficient image with the low-frequency coefficients and high-frequency coefficients: for low-frequency co...

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Abstract

The invention discloses a feature-level medical image fusion method based on 3D (three dimension) shearlet transform, belonging to the technical field of medical image processing and application. The feature-level medical image fusion method mainly comprises the following steps: 1, performing 3D-D-CSST (three dimensional-discrete-compact shearlet transform) or 3D-DT-CSST (three dimensional dual-tree compact shearlet transform) on two images to obtain transformation coefficient images Ca and Cb; 2, performing image fusion on transformation coefficients to obtain a fusion coefficient Cf; and 3, performing DWT or DTCWT inverse transformation, performing backward shear transformation on the transformed image to obtain a fusion image Vf. According to the feature-level medical image fusion method, the problems that the quality of a fused image is relatively low and information which is partially important and is not remarkable is easily ignored are solved.

Description

technical field [0001] The invention belongs to the technical field of medical image processing and application, and specifically relates to a feature-level medical image fusion method based on 3D shearlet transform, which solves the problem that the quality of the fused image is relatively low and locally important but insignificant information is easily overlooked . Background technique [0002] Medical image fusion is a kind of image fusion, and many methods have been widely used in clinical diagnosis. Fusion refers to the process of extracting and merging important information about the target from source images collected by different devices such as CT and MRI into one image. The information contained in images generated by different devices or different configurations of the same device is different, some information is similar, but most of the information is complementary. For example, CT images mainly provide information on dense and hard tissues of the human body,...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/50G06T3/40A61B6/03A61B5/055
Inventor 王帅段昶刘想程建
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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