Discrete Radon projection and Mojette projection conversion method based on fixed resolution

Abstract

A discrete Radon projection and Mojette projection conversion method based on a fixed resolution is disclosed, which belongs to the technical field of computer imaging in the field of image processing. The discrete Radon projection and Mojette projection conversion method is characterized by converting a sparse angle discrete Radon projection under an actual imaging condition into a Mojette projection which is accurately reconstructed in a discrete domain. Based on the computer tomography imaging algorithm, Radon and Mojette projection scenes are simulated by constructing a reasonable imaging system; and after the relation between the Mojette projection and the Radon projection is analyzed in detail, a specific algorithm of converting the Radon projection into the Mojette projection under a corresponding projection vector at each projection angle on the premise of a given fixed resolution. The discrete Radon projection and Mojette projection conversion method has the effects and the benefits that at different sparse projection angles, the resolution of an Radon projection image does not need to be changed; the conversion disorder between variation of the resolution of a Mojette projection domain along with the projection vector and the constant resolution of the Radon projection is overcome; and a conversion bridge between the two projections is set up.

Description

technical field [0001] The invention belongs to the technical field of computer tomography (CT) in the field of image processing, and relates to the problem of sparse sampling and high-efficiency restoration in the image projection transformation domain. Background technique [0002] CT technology is a computer-based three-dimensional reconstruction technology that can reproduce the invisible internal slice structure of an object without damaging the surface and internal structure of the object. In terms of CT imaging algorithms, according to the different imaging principles, it is divided into analytical and iterative reconstruction algorithms; according to the reconstruction accuracy, it is divided into approximate reconstruction and precise reconstruction algorithms. In the analytical algorithm, the transformation model proposed by the Austrian mathematician Radon uses low-dimensional compressed projection data to reconstruct the high-dimensional object structure. This ma...

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Problems solved by technology

[0003] However, since the imaging system is a digital discrete system, the continuous projection model cannot be applied to discrete images, so the discrete Radon transform randomly emerges

The discrete Radon transform and its inverse transform solve the problem of converting from the analog domain to the digital domain, but the reconstruction algorithm based on the inverse Radon transform requires a large number of sampling samples and projections to reconstruct a better reconstructed fault. It will lead to too high radiation dose and too long reconstruction time. Considering that the patient's health and the dynamic changes of lesions in medical imaging will cause artifacts, it is necessary to perform high-quality imaging in a short time, low dose and sparse angle. important, yet challenging

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