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首页> 外文会议>Biennial Australian Pattern Recognition Society Conference(DICTA2003) v.2; 2003; Sydney; AU >Compression of Dynamic PET Based on Principal Component Analysis and JPEG 2000 in Sinogram Domain
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Compression of Dynamic PET Based on Principal Component Analysis and JPEG 2000 in Sinogram Domain

机译：基于Singram域主成分分析和JPEG 2000的动态PET压缩

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摘要

A new algorithm for the compression of dynamic positron emission tomography (PET) data is presented. It consists of a temporal compression stage based on the application of principal component analysis (PCA) directly to the PET sinograms to reduce the dimensionality of the data. This is followed by a spatial compression stage using JPEG 2000 to each PCA channel weighted by the signal in each channel. By combining these temporal and spatial compression techniques we can achieve a compression ratio as high as 129:1 while simultaneously reducing noise and improving functional estimation compared with the uncompressed data, and preserving the sinogram data for later analysis. We validate our approach with a simulated phantom FDG brain study and clinical dynamic PET datasets. The results of performance evaluation suggest the new compression technique not only is able to reduce the original sinogram datasets by more than 95%, but also improve the reconstructed image quality for the quantitative analysis.
机译：提出了一种新的动态正电子发射断层扫描（PET）数据压缩算法。它由基于主成分分析（PCA）的时间压缩阶段直接应用于PET正弦图来减少数据的维数。随后是对每个PCA通道使用JPEG 2000的空间压缩阶段，该通道由每个通道中的信号加权。通过结合这些时间和空间压缩技术，与未压缩的数据相比，我们可以实现高达129：1的压缩比，同时降低噪声并改善功能估计，并保留正弦图数据以供以后分析。我们通过模拟的幻像FDG脑研究和临床动态PET数据集验证了我们的方法。性能评估结果表明，新的压缩技术不仅能够将原始的正弦图数据集减少95％以上，而且还可以改善重建的图像质量以进行定量分析。

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