The Application of Principal Component Analysis to the Separation of Multiple Tracers in PET Images

Wang Zhen-you; Zheng Shao-jie; He Yuan-cai; Long Jie-li; Su Na; Lin Jie-zhi

doi:10.3969/j.issn.1007-7162.2013.02.009

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The Application of Principal Component Analysis to the Separation of Multiple Tracers in PET Images

更新时间：2026-05-27

- The Application of Principal Component Analysis to the Separation of Multiple Tracers in PET Images
- Vol. 30, Issue 2, Pages: 42-46(2013)
- 作者机构：
- 作者简介：
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- DOI：10.3969/j.issn.1007-7162.2013.02.009
  CLC：
- Online First：27 June 2013，
  
  Published：2013
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王振友, 郑少杰, 何远才, 龙洁丽, 苏娜, 林洁芝. 基于PCA方法的PET图像多示踪剂分离[J]. 广东工业大学学报, 2013, 30(2): 42-46.

Wang Zhen-you, Zheng Shao-jie, He Yuan-cai, et al. The Application of Principal Component Analysis to the Separation of Multiple Tracers in PET Images[J]. 2013, 30(2): 42-46.
王振友, 郑少杰, 何远才, 龙洁丽, 苏娜, 林洁芝. 基于PCA方法的PET图像多示踪剂分离[J]. 广东工业大学学报, 2013, 30(2): 42-46. DOI： 10.3969/j.issn.1007-7162.2013.02.009.

Wang Zhen-you, Zheng Shao-jie, He Yuan-cai, et al. The Application of Principal Component Analysis to the Separation of Multiple Tracers in PET Images[J]. 2013, 30(2): 42-46. DOI： 10.3969/j.issn.1007-7162.2013.02.009.

摘要

将PCA方法应用在PET肿瘤图像的多示踪剂曲线分离.首先是对两种不同的示踪剂在带噪声的情况下提取贡献率达到95%以上的主分量，然后根据示踪剂注射时间的延迟和示踪剂的主分量建立方程组，再用最小二乘法求得主分量的系数，最后得出3种示踪剂的曲线.通过实验模拟进行了数据验证，结果表明该方法是可行的.经核算，求出的结果与原数据的一致性检验达到80%以上.

Abstract

It studies the application of PCA to the separation of multiple tracers in PET tumour images. First

up-to-95% contribution rate principal components were extracted from two different tracers under noisy circumstances

and then an equation set was established

based on time difference between different tracers and their principal components. and injection -time delay and principal components of the tracers. Then

the coefficient of principal components was obtained via linear least square. Finally

three kinds of tracer curves were attained. Experimental results show that the relative data are feasible

and the consistency between the result and raw data comes to a satisfactory 80%.

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