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PET image reconstruction method and system

An image reconstruction and image technology, which is applied in the field of medical imaging, can solve the problems of poor image quality, poor contrast, and cannot guarantee the global optimality of regularization parameters, and achieves the effect of strong applicability and improved quality.

Pending Publication Date: 2021-03-19
JIANGSU SINOGRAM MEDICAL TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The quality of the reconstructed image is usually sensitive to the selection of regularization parameters. When the regularization parameter is large, although the noise can be reduced and the PET image is smooth as a whole, but the edges are blurred and the contrast is poor; Edge contrast, but noisy and poor image quality
Unfortunately, there is no intuitive correspondence between regularization parameters and image quality, so the selection of parameter values ​​is often based on experience, and then the image quality is verified through experiments, and then a better result is compared and selected. Not only is the operation complicated and time-consuming, but the evaluation criteria Not objective, and there is no guarantee that the regularization parameters are globally optimal

Method used

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  • PET image reconstruction method and system

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Effect test

Embodiment 1

[0072] like figure 1 As shown, the embodiment of the present invention provides a PET image reconstruction method. During the PET image reconstruction process, its execution subject can be a PET computing device, for example, it can be a computing device belonging to a multi-modal PET system, or it can be a separate computer etc. The method of the present embodiment comprises the following steps:

[0073] In step 101, the PET calculation device acquires detection data in the detection device.

[0074] Step 102 , the PET calculation device acquires a regularized objective function Φ(x,y)=L(x,y)−β·R(x) for reconstructing an image according to the detection data.

[0075] Among them, L(x,y) is the likelihood function item corresponding to the detection data, R(x) is the prior knowledge item, and β is the regularization parameter, which is used to adjust the weight of L(x,y) and R(x) ;

[0076] Specifically, in this step, the PET calculation device can construct the following ...

Embodiment 2

[0091] The present invention proposes a method for PET image reconstruction. In the steps of the method, prior knowledge can be introduced in the iterative process and the regularization parameters can be automatically adjusted, so that the iterative result is close to the ideal value and the tedious manual selection of parameters is reduced. , making the selection of regularization parameters more concise and accurate. The specific steps of this method are as follows:

[0092] Step 1: The PET acquisition process can be modeled as the following formula:

[0093]

[0094] In the formula, y=[y 1 ,y 2 ,...,y N ] T Indicates the detected data, and N indicates the dimension of the detected data. For listmode reconstruction, N is the number of detected cases; for sinogram-based reconstruction, N is the size of the sinogram; if the acquisition case includes time resolution TOF (Time of Flight) information, N should also include the dimension of time resolution discretization....

Embodiment 3

[0148] According to another aspect of the embodiments of the present invention, the embodiments of the present invention further provide a computing device, including: a memory, a processor, and a bus, and the processor is connected to the memory through the bus;

[0149] The memory is used to store a program, and the processor is used to run the program, wherein the method for reconstructing a PET image described in any one of Embodiment 1 and Embodiment 2 is executed when the program is running.

[0150] According to the third aspect of the embodiments of the present invention, the embodiments of the present invention further provide a PET system, including: a PET detection data collection device and the computing device described in any one of the second aspects.

[0151] The above-mentioned PET system can perform image reconstruction processing through a computing device after scanning with a PET detection data acquisition device, and can obtain a high-quality PET image tha...

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Abstract

The invention relates to a PET image reconstruction method and system. The method comprises the steps that 101, PET computing equipment acquires detection data in detection equipment; 102, the PET computing equipment acquires a regularization target function phi(x, y) = L(x, y)-beta * R(x) for reconstructing an image according to the detection data, wherein L(x, y) is a likelihood function item corresponding to the detection data, R(x) is a priori knowledge item, and beta is a regularization parameter and is used for adjusting the weights of L(x, y) and R(x); 103, the PET computing equipment determines a parameter beta in a regularization target function according to the signal-to-noise ratio information and the input parameter of the detection data; 104, the PET computing equipment reconstructs a PET image according to the determined parameter beta and the regularization target function, and finally the purpose of improving the quality of the reconstructed PET image is achieved.

Description

technical field [0001] The invention relates to the technical field of medical imaging, in particular to an image reconstruction method and system which can be used in a positron emission computed tomography imaging system. Background technique [0002] Positron Emission Tomography PET (Positron Emission Tomography) is a high-end nuclear medicine imaging diagnostic equipment. In practice the use of radionuclides (eg 18 F. 11 C, etc.) Label the metabolites and inject the nuclides into the human body, and then perform functional metabolic imaging on the patient through the PET system to reflect the metabolic activities of life, so as to achieve the purpose of diagnosis. Currently commercial positron emission tomography PET is usually integrated with other modal imaging systems, such as computed tomography CT (Computed Tomography) or magnetic resonance imaging MRI (Magnetic Resonance Imaging), to achieve the purpose of simultaneously imaging the patient's anatomical structure...

Claims

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Application Information

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IPC IPC(8): G06T11/00
CPCG06T11/006G06T2211/412G06T2211/424
Inventor 崔洁李楠
Owner JIANGSU SINOGRAM MEDICAL TECH CO LTD
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