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Compressive sensing computer tomography image reconstruction method based on p-norm

A compressed sensing and tomography technology, which is applied in the field of image processing of medical images, can solve the problems of confusion and ghosting, time-consuming algorithms, etc., and achieves the effect of reducing scanning time, X-ray exposure time, and expanding the scope of clinical applications.

Active Publication Date: 2015-08-26
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0006] Technical problem: The purpose of the present invention is to provide a P-norm-based compressed sensing CT image reconstruction method, which overcomes the heavy confusion and ghosting of the algebraic iteration method in CT images and the time-consuming algorithm in the case of incomplete sampling data, etc. Cons, ensuring reconstructed image quality

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Embodiment Construction

[0016] First, the CT projection data is acquired and initialized, including sparse transformation and image sampling; then, m rounds of image iterative reconstruction with total variation adjustment are performed on the initialized projection data. Adjust the image after iteration to minimize the Lp norm of the total variation of the image, and judge whether the iteratively reconstructed image of the nth (0<n<m) round satisfies the iteration convergence condition. If the iteration convergence condition is not satisfied, continue to iterate; If satisfied, the reconstructed image will be saved and output.

[0017] The wavelet sparse transform implements the sparse representation of the sampled image data. Image sampling refers to image sampling using a local Fourier transform matrix that satisfies the constraint equidistant condition and is irregular.

[0018] The total variation TV of the image is shown in formula 1)

[0019] TV ( x ...

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Abstract

The invention discloses a compressive sensing computer tomography image reconstruction method based on a p-norm, and particularly to a CT image algebraic reconstruction method which performs image total variation Lp norm minimizing on incomplete projection data. The method mainly comprises the steps of (1) acquiring a CT system imaging parameter and scanning system projection data; (2) initializing the projection data, performing discrete processing and filtering noise-reduction processing on the projection data by means of a wavelet transformation base, solving a projection matrix through weighting and performing assignment x(0)=0 on an initial image x; and (3) performing algebraic reconstruction on the projection data, performing total variation Lp norm minimizing adjustment on the image after iteration each time by means of a gradient decent algorithm, and determining whether a convergence condition is satisfied. If the convergence condition is satisfied, the reconstructed image is stored and output; and otherwise, continuing iteration in a manner that the adjusted image which is iterated this time as an interaction initial value.

Description

technical field [0001] The present invention relates to the field of image processing of medical images, in particular to computerized tomography (CT), in particular to a P-norm-based compressive sensing CT image reconstruction method, which can realize high-resolution reconstruction from incomplete scan data. CT images with high signal-to-noise ratio and high definition. The problem of aliasing artifacts and large noise in the reconstructed image can be improved, thereby reducing the X-ray radiation time and shortening the image reconstruction time. Background technique [0002] Computed tomography is a digital imaging technique that combines computer technology and radiation detection technology. Has been widely used in industrial testing and medical diagnosis. The pursuit of high-quality CT images often requires placing the measured object under X-ray irradiation for a long time, thus damaging the measured object. [0003] Radon transformation and inverse transformatio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00
Inventor 喻春雨谈新缪亚健费彬
Owner NANJING UNIV OF POSTS & TELECOMM
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