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Formation of Parametric Images in Positron Emission Tomography Using a Clustering-Based Kinetic Analysis With Statistical Clustering.

机译:利用基于聚类的动力学分析统计聚类在正电子发射层析成像中形成参数图像。

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摘要

A method is proposed for forming parametric images in position emission tomography, using clustering kinetic analysis. To overcome the dual problems experienced in voxel-based data, of signal noise and the very long computational time, the data are clustered before parameter estimation, and then estimation procedure is applied to the averaged data in each cluster. Using this algorithm, PET data are optimally clustered, depending on the noise that is present, by hierarchically applying a statistical-clustering algorithm based on Mixed Gaussian model. In a computer simulation, the proposed method correctly clustered noise-contaminated data. Applying the proposed algorithm to (18)F-FDG clinical data, physiologically acceptable parametric images of glucose metabolism in a brain were obtained in a practical calculation time.

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