Image Restoration Method of CT Sequence Based on Low Rank Decomposition

A sequence image and low-rank decomposition technology, applied in the field of medical image processing, can solve problems such as poor restoration effect and affect the visual effect of CT images, and achieve accurate restoration results

Active Publication Date: 2016-04-13
XIDIAN UNIV
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Problems solved by technology

However, for CT images with large noise content, the restoration effect of this method is poor
Because the inverse filter sharpens the image and amplifies the useless noise, which seriously affects the visual effect of the CT image.

Method used

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  • Image Restoration Method of CT Sequence Based on Low Rank Decomposition
  • Image Restoration Method of CT Sequence Based on Low Rank Decomposition
  • Image Restoration Method of CT Sequence Based on Low Rank Decomposition

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Embodiment Construction

[0025] refer to figure 1 , the present invention is based on the CT sequence image restoration method of low-rank decomposition and comprises the following steps:

[0026] Step 1: Input CT sequence image I i , i=1,...,k, k is an integer greater than 1, if the sequence image I i If it is a color image, convert it to a grayscale image, otherwise, proceed to step (2) directly; this CT sequence image is derived from the chest CT sequence of the patient, the size is 512×512, and it is an RGB image, such as figure 2 shown.

[0027] Step 2: Select a low-rank model pair sequence image I i Perform sparse low-rank decomposition to obtain low-order sequence L i and the sparse sequence S i .

[0028] 2a) The CT sequence image I i All image matrices in are synthesized into a high-dimensional matrix, and each column in the high-dimensional matrix represents a CT image in the sequence;

[0029] 2b) According to the size of CT sequence image noise, select the corresponding low-rank m...

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Abstract

The invention discloses a CT sequential image restoration method based on low rank decomposition. The CT sequential image restoration method mainly solves the problem that the instability of CT sequential image restoration in the prior art easily causes noise amplification and image distortion. The CT sequential image restoration method is implemented in the following steps: (1) a CT sequential image is converted into a grayscale image first; (2) a low rank model is selected to conduct sparse low rank decomposition on a CT sequence, wherein a corresponding low rank model is selected to conduct sparse low rank decomposition on a CT image according to the noise amplitude of the CT image; (3) an average image of a low rank sequence is obtained, and a two-dimensional Gaussian blurring core is used for conducting Wiener filtering restoration on the average image; (4) a disturbance blurring core is used for conducting Wiener filtering restoration on each image in a sparse sequence; (5) all the images in the restored sparse sequence are merged with a restored low rank image to obtain a restored CT sequential image. Compared with a traditional CT restoration method, the CT sequential image restoration method based on low rank decomposition has the advantages that the accuracy is high, the adaptability is good, and the restoration effect is not limited by the noise amplitude of the CI image.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to restoration of CT sequence images, which can be used for processing medical images. Background technique [0002] With the rapid development of medical imaging technology, a large number of high-resolution images have emerged, such as magnetic resonance imaging MRI, computed tomography CT, magnetoencephalography MEG, three-dimensional ultrasound imaging, solution positron emission tomography PET, single photon emission computed tomography SPECT, diffusion weighted imaging DWI, functional magnetic resonance FMRI, etc., these imaging techniques have their own characteristics, and they can provide people with various anatomical and functional information at different temporal and spatial resolutions. However, relying solely on the information provided by these devices is far from meeting people's requirements, and the image must be further analyzed and interpreted by means ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 缑水平焦李成王越越刘芳张晓鹏王之龙唐磊周治国
Owner XIDIAN UNIV
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