Improved multi-sequence magnetic resonance image registration method based on self-similarity

A magnetic resonance image, self-similar technology, applied in image enhancement, image analysis, image coding and other directions, can solve the problems of poor stability, poor conversion map effect of multi-sequence magnetic resonance medical images, etc., to ensure the registration accuracy, The effect of good registration stability and faster noise reduction

Active Publication Date: 2019-02-22
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the shortcomings of the existing multi-sequence magnetic resonance image registration method in the case of noise, the conversion map effect of the multi-sequence magnetic resonance...

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  • Improved multi-sequence magnetic resonance image registration method based on self-similarity
  • Improved multi-sequence magnetic resonance image registration method based on self-similarity
  • Improved multi-sequence magnetic resonance image registration method based on self-similarity

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings.

[0042] refer to figure 1 , an improved multi-sequence magnetic resonance image conversion method based on self-similarity, comprising the following steps:

[0043] 1) For the three-dimensional magnetic resonance images of all sequences, use the non-local mean fast denoising algorithm to denoise layer by layer;

[0044] 2) Extract the foreground part through the stacked Otsu algorithm, that is, use the Otsu algorithm multiple times to superimpose the latter foreground into the previous image;

[0045] 3) Use local 3D median filtering to optimize the result, fill in some pixels that are mistaken for the background and ignore them, and smooth some prominent pixels:

[0046] 4) Use self-similarity to encode the preprocessed image, the process is as follows:

[0047] 4.1) Select the 6 pixels closest to a pixel, and select the difference between 12 pairs of pixels whose d...

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Abstract

An improved multi-sequence magnetic resonance image registration method based on self-similarity comprises the following steps: 1) de-noising all three-dimensional magnetic resonance images layer by layer using a non-local mean fast de-noising algorithm; 2) extracting the foreground part by using the cascading Otsu algorithm, that is, using the Otsu algorithm for many times to superimpose the foreground part on the previous image; 3) using local three-dimensional median filter to optimize the result; 4) encoding that preprocessed image by use self-similarity; 5) using a discrete-based optimization method to calculate similarity measure between feature images, and judge whet that similarity measure reaches the optimal state; 6) using the final transformation matrix to transform the originalfloating image to obtain the final result map. The invention has strong anti-noise interference ability and high registration accuracy.

Description

technical field [0001] The invention relates to a multi-sequence magnetic resonance image registration method. Background technique [0002] Usually, the registration between different sequences of magnetic resonance images is to optimize the similarity measure through the similarity measure and optimization algorithm, and always find the best similarity measure value. The image registration method determines the degree of similarity between images of different sequences through the similarity measure, but the similarity measure ignores the structural information existing between the images. When the similarity measure between different sequences of magnetic resonance images falls into a local optimum , tends to output a different result than what a human visually should get. At present, there are many kinds of image registration, such as the research based on similarity measure, such as the image registration method based on mutual information, the mutual information image...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/50G06T7/136G06T7/194G06T7/30G06T9/00
CPCG06T5/002G06T5/50G06T9/00G06T2207/20032G06T2207/20182G06T2207/20221G06T2207/20224G06T7/136G06T7/194G06T7/30
Inventor 管秋陈奕州金钦钦李康杰黄志军王捷龚明杰袁梦依陈胜勇
Owner ZHEJIANG UNIV OF TECH
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