Method and device for reconstructing GPU (Graphic Processing Unit) accelerating X-ray image based on CUDA (Compute Unified Device Architecture)

Abstract

The invention discloses a method and a device for reconstructing a GPU (Graphic Processing Unit) accelerating X-ray image based on a CUDA (Compute Unified Device Architecture). The method comprises the following steps: transmitting acquired X-ray image projection data into a CPU (Central Processing Unit) memory by virtue of a CPU; partitioning the X-ray image projection data into multiple projection data regions by virtue of GPU, partially overlapping the adjacent projection data regions, and sending the multiple projection regions to the CPU memory; performing tomographic reconstruction on each projection data region by virtue of a GPU parallel kernel function accelerating shift and add algorithm, so as to obtain corresponding partial reconstruction images; splicing and synthesizing the partial reconstruction images into the reconstruction image. According to the method and the device, the parallel shift and add algorithm is realized by virtue of GPU hardware acceleration under the CUDA, so that the computing speed is greatly improved, meanwhile the cost is saved, and great convenience is brought to a user.

Description

technical field [0001] The present invention relates to the field of medical image processing, in particular to a GPU-accelerated X-ray image reconstruction method and device based on CUDA architecture. Background technique [0002] With the continuous development of X-ray equipment, the existing X-ray devices pass through the ball tube and the flat panel, and in the case of a fixed SID (X-ray device system identification code system identification), emit rays through a scan of the linear array tube to obtain Multi-frame X-ray images. Then the tomographic image is reconstructed through the shift and add algorithm for multiple frames of X-ray images. However, the traditional serial shift and add algorithm or the FPGA hardware-accelerated shift and add algorithm are used for image reconstruction, but the serial shift and add algorithm for image reconstruction takes too long, while FPGA hardware-accelerated shift and add Add algorithm to image reconstruction method hardware ...

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a GPU-accelerated X-ray image reconstruction method and device based on the CUDA architecture for the above-mentioned defects of the prior art, aiming to solve the problems caused by the excessive data volume in the existing X-ray image reconstruction technology. The problem that the algorithm takes too long and the hardware cost is too high caused by large

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