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Study of CT Images Processing with the Implementation of MLEM Algorithm using CUDA on NVIDIA’S GPU Framework

机译:在NVIDIA GPU框架上使用CUDA实现MLEM算法的CT图像处理研究

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In medicine, the acquisition process in Computed Tomography Images (CT) is obtained by a reconstruction algorithm. The classical method for image reconstruction is the Filtered Back Projection (FBP). This method is fast and simple but does not use any statistical information about the measurements. The appearance of artifacts and its low spatial resolution in reconstructed images must be considered. Furthermore, the FBP requires of optimal conditions of the projections and complete sets of data. In this paper a methodology to accelerate acquisition process for CT based on the Maximum Likelihood Estimation Method (MLEM) algorithm is presented. This statistical iterative reconstruction algorithm uses a GPU Programming Paradigms and was compared with sequential algorithms in which the reconstruction time was reduced by up to 3 orders of magnitude while preserving image quality. Furthermore, they showed a good performance when compared with reconstruction methods provided by commercial software. The system, which would consist exclusively of a commercial laptop and GPU could be used as a fast, portable, simple and cheap image reconstruction platform in the future.
机译:在医学上,计算机断层扫描图像(CT)中的采集过程是通过重建算法获得的。图像重建的经典方法是反滤波(FBP)。这种方法既快速又简单,但是不使用有关测量的任何统计信息。必须考虑伪像的出现及其在重构图像中的低空间分辨率。此外,FBP需要最佳的投影条件和完整的数据集。本文提出了一种基于最大似然估计方法(MLEM)的CT加速采集过程的方法。此统计迭代重建算法使用GPU编程范例,并与顺序算法进行了比较,在序列算法中,在保留图像质量的同时,重建时间最多减少了3个数量级。此外,与商用软件提供的重建方法相比,它们显示出良好的性能。该系统将完全由商用笔记本电脑和GPU组成,将来可以用作快速,便携式,简单和廉价的图像重建平台。

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