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CT reconstruction method based on fractal and compressed sensing

A compressed sensing and fractal technology, applied in 2D image generation, instrumentation, calculation, etc., can solve the problem of reducing the signal-to-noise ratio of CT images, and achieve the effect of improving imaging quality and avoiding data rearrangement.

Active Publication Date: 2017-12-01
CHONGQING UNIV
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Problems solved by technology

Using the first method will lead to a decrease in the signal-to-noise ratio of the CT image, and the image reconstructed by the second method will have more artifacts. However, as the compressed sensing theory is widely used in CT image reconstruction, people often use the second method. A method to reduce the dose of X-ray radiation

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  • CT reconstruction method based on fractal and compressed sensing
  • CT reconstruction method based on fractal and compressed sensing
  • CT reconstruction method based on fractal and compressed sensing

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Embodiment Construction

[0027] The principle of the present invention is further described below as a realization method:

[0028] 1. Principle of CT and Compressed Sensing

[0029] The principle of CT is as figure 1 As shown, the X-ray intensity emitted by the X-source is I 0 , because the energy of the X-ray is very high and can penetrate the scanned object, the intensity of the X-ray emitted is I 1 , according to the lambert-beer law we have

[0030] I 1 =I 0 e -∫μds (1)

[0031] Among them, μ is the attenuation coefficient corresponding to the attenuation of the X-ray passing by the scanned object on the X-ray path. Different substances have different attenuation coefficients, and CT is precisely by mapping the attenuation coefficient of the object to the gray value to obtain CT. image u.

[0032] By processing formula (1), we can get

[0033]

[0034] in is the projection data, that is, the projection data is the line integral of the X-ray attenuation coefficient on the X-ray opti...

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Abstract

A CT reconstruction method based on fractal and compressed sensing, including steps: (1) known CT projection data b and corresponding projection angle θ, initialization parameters β, λ, λn, CT image u=0; (2) according to the projection Angle θ, calculate the corresponding projection matrix A; (3) Use formula (5) to calculate CT image uART; (4) Perform fractal coding on uART to get Φ(u), use formula (12) to get α; (5) Perform decoding processing on Φ(u) to get ΦT(u); 6) Solve ΦT(u)Φ(u), ΦT(u)α, ATA, ATb respectively; (7) Use conjugate gradient method to solve equation (15) , get the CT image 8) Check whether the condition for the end of the iteration is met, go to step (9), otherwise step (3); (9) ends, the output CT image method uses fractal as a sparse transformation to obtain a more sparse coefficient representation, Iterative continuous iterative algorithm is used to solve the problem, and high-quality CT images can be reconstructed with less projections.

Description

technical field [0001] The invention relates to the technical field of tomographic image reconstruction, in particular to a low-dose CT reconstruction algorithm. Background technique [0002] Since its inception in 1973, CT (computed tomography) has been widely used in medical diagnosis, industrial non-destructive testing and other fields, especially playing a pivotal role in medical diagnosis. However, the light source used in CT is X-rays, which are harmful to the human body, and may cause diseases such as gene mutation and cancer. Therefore, it is imperative to reduce the dose of X-ray radiation as much as possible. There are two basic ideas for reducing the dose of X-ray radiation. First, reduce the intensity of X-rays. Second, reducing the number of X-ray projections means reducing the number of projections. Using the first method will reduce the signal-to-noise ratio of CT images, and the images reconstructed by the second method will have more artifacts. However, wi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00A61B6/03
Inventor 陈绵毅冯鹏魏彪何鹏张伟邓露珍米德伶
Owner CHONGQING UNIV
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