CUDA-based PET system matrix calculation method

Abstract

The invention discloses a CUDA-based PET system matrix calculation method. The method comprises the following steps: firstly, dividing a detector system according to a fixed angle to obtain response line equations of subsets after division; then, allocating a grid to each angle in CUDA, allocating a block to each sub-response line at each angle, transmitting pixel coordinate data of the reconstructed image to a shared memory of each block, and calculating a probability weight of each pixel rapidly and parallelly by threads in the blocks, wherein the grids are sequentially and serially executed, and different blocks in the same grid are quickly and parallelly executed; and finally, splicing the probability weights within angles to obtain a system matrix subset, and splicing the system matrix subset to obtain a system matrix. According to the method, on the premise of ensuring the accuracy of system matrix elements, the creation efficiency is improved, and the problems caused by low system matrix creation speed, limited GPU video memory resources and large system matrix data volume are solved.

Description

technical field [0001] The invention belongs to the field of radiation detection and imaging, and in particular relates to a PET system matrix calculation method. Background technique [0002] Positron emission tomography (Posintron Emission Tomography, PET) is a non-invasive nuclear medicine imaging diagnosis technology widely used in clinical practice. It provides functional information such as metabolism of the living body by imaging the radioactive tracer injected into the living body . At present, PET is mainly used in the field of medical diagnosis, and there is less research in the industrial field. Gamma photons have strong penetrability and electrical neutrality, and are less affected by factors such as materials, structures, and electromagnetic fields. Therefore, it is of great significance to apply PET technology to the field of industrial nondestructive testing. The main working process of the PET system: [0003] (1) The detector obtains matching data: the de...

AI Technical Summary

Problems solved by technology

Although the system matrix is ​​extremely important in the image reconstruction process, its generation speed is very slow due to the large amount of calculation, which is difficult to meet the requirements of fast industrial inspection.

The size of the system matrix is ​​related to the number of PET detectors and the size of the reconstructed slice map. Due to the large amount of data, its generation speed has always been a difficulty. It is difficult to guarantee a significant increase in speed simply by improving on the CPU.

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