Optimization method of CT iterative reconstruction cost function, CT image reconstruction method and system, and CT

Abstract

The invention belongs to the technical field of CT reconstruction, and particularly relates to an optimization method of a CT iterative reconstruction cost function, which converts a potential function into a pixel independent potential function by using the convex characteristic of a qGGMRF regularization model, so that the derivative of the potential function to each pixel point is only related to the current pixel point and is irrelevant to other pixel points in a CT image, mutual separation of all the pixel points in the q-GGMRF regularization model is achieved, it is guaranteed that optimization of all the pixel points can be conducted at the same time, consumed time of iterative reconstruction is effectively shortened, and the clinical requirement for timeliness is met.

Description

technical field [0001] The invention belongs to the technical field of CT reconstruction, and in particular relates to an optimization method of a CT iterative reconstruction cost function, a CT image reconstruction method, a system and a CT. Background technique [0002] Computer X-ray tomography scanner, referred to as CT, uses X-ray rotation to irradiate the measured object, and then obtains the tomographic image of the object through computer processing; among them, the process of obtaining the tomographic image of the object by processing the scanned data is called CT reconstruction. [0003] Existing algorithms for CT reconstruction generally include two categories: filtered back projection (FBP) and iterative reconstruction. As CT is used more and more widely and frequently in clinic, the X-ray radiation that the scanned patients bear is also increasing. In order to reduce the risk of lesions caused by X-ray radiation, low-dose CT has received more and more attention...

AI Technical Summary

Problems solved by technology

Since the number of pixels in CT images is on the order of millions, the reconstruction process is very time-consuming, usually taking several hours or even dozens of hours, which is difficult to meet the clinical timeliness requirements

[0016] The U.S. patent with the publication number US20130010917A1 proposes a CT iterative reconstruction algorithm, which still uses the ICD algorithm to optimize the cost function using q-GGMRF as the regular term; further, in order to reduce the calculation time, it proposes the The update replaces the line search with a quadratic substitution function, and stores the derivative of the potential function as a lookup table in advance, occupying storage space; although it can reduce the calculation time, the effect is limited, and the iterative reconstruction time is still about hours The measurement of the unit is also difficult to meet the clinical timeliness requirements

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