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CT reconstruction method based on fractal and compression sensing

A compressive sensing and fractal technology, applied in the generation of 2D images, instruments, calculations, etc., can solve the problem of reduced signal-to-noise ratio of CT images, achieve the effect of improving imaging quality and avoiding data rearrangement

Active Publication Date: 2015-02-18
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 compression sensing

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[0027] The following further explains the principle of the present invention is the realization method:

[0028] 1. CT principle and compressed sensing

[0029] The principle of CT is as figure 1 As shown, the X-ray intensity emitted by the X-ray source is I 0 , Because the X-ray energy is very high and can penetrate the object being scanned, the emitted X-ray intensity 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 materials have different attenuation coefficients, and CT is the attenuation coefficient of the object mapped to the gray value to obtain CT Image u.

[0032] To deal with (1), we can get

[0033] ln I 0 I 1 = ∫ μds - - - ( 2 )

[0034] among them Is the projection data, that is, the projection data is the line integral of the X-ray attenu...

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Abstract

The invention provides a CT reconstruction method based on fractal and compression sensing. The method includes the steps that (1) CT projection data b, a corresponding projection angle theta and initialization parameters beta, lambda and lambda n are known, and a CT image u is equal to zero; (2) a corresponding projection matrix A is calculated according to the projection angle theta; (3) a CT image uART is calculated by means of a formula (5); (4) fractal encoding processing is carried out on uART, so that fai (u) is obtained, and alpha is obtained by means of a formula (12); (5) decoding processing is carried out on the fai (u), so that fai T(u) is obtained; (6) fai T(u), fai (u), fai T(u) alpha, ATA and ATb are solved; (7) a formula (15) is solved in a conjugate gradient method, and accordingly a CT image is obtained; (8) whether a condition of finishing iteration is met is detected, if the answer is positive, a step (9) is carried out and otherwise the step (3) is carried out; (9) operations are finished, and the CT image is output. According to the method, fractal serves as sparse transform so that a more sparse coefficient representation can be obtained, an alternating and continuity algorithm is used for obtaining solutions and the high-quality CT image is constructed on the condition that a little of projection exists.

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 in the medical diagnosis to play a pivotal role. However, the light source used in CT is X-rays that are harmful to the human body, which may cause genetic mutations, cancer and other diseases, so it is imperative to reduce the X-ray radiation dose as much as possible. There are two basic ideas for reducing X-ray radiation dose. First, reduce the intensity of X-rays. Second, fewer X-ray projections reduce the number of projections. Using the first method will cause the signal-to-noise ratio of CT images to decrease, and the images reconstructed by the second method will have more artifacts. However, as the compressed sensing theory...

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Application Information

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Patent Type & Authority Applications(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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