@article{16ba8024d8fc457f860addd7707d55c0,
title = "Clustering-based linear least square fitting method for generation of parametric images in dynamic FDG PET studies",
abstract = "Parametric images generated from dynamic positron emission tomography (PET)studies are useful for presenting functional/biological information in the3-dimensional space, but usually suffer from their high sensitivity to image noise.To improve the quality of these images, we proposed in this study a modified linear least square (LLS) fitting method named cLLS that incorporates a clustering-based spatial constraint for generation of parametric images from dynamic PET data of high noise levels. In this method, the combination of K-means and hierarchical cluster analysis was used to classify dynamic PET data.Compared with conventional LLS, cLLS can achieve high statistical reliability in the generated parametric images without incurring a high computational burden.The effectiveness of the method was demonstrated both with computer simulation and with a human brain dynamic FDG PET study. The cLLS method is expected to be useful for generation of parametric images from dynamic FDG PET study.",
author = "Xinrui Huang and Yun Zhou and Shangliang Bao and Huang, {Sung Cheng}",
note = "Funding Information: Parametric images generated from dynamic positron emission tomography (PET) studies are useful for presenting functional/biological information in the 3-dimensional space, but usually suffer from their high sensitivity to image noise. To improve the quality of these images, we proposed in this study a modified linear least square (LLS) fitting method named cLLS that incorporates a clustering-based spatial constraint for generation of parametric images from dynamic PET data of high noise levels. In this method, the combination of K-means and hierarchical cluster analysis was used to classify dynamic PET data. Compared with conventional LLS, cLLS can achieve high statistical reliability in the generated parametric images without incurring a high computational burden. The effectiveness of the method was demonstrated both with computer simulation and with a human brain dynamic FDG PET study. The cLLS method is expected to be useful for generation of parametric images from dynamic FDG PET study. National Basic Research Subject of China 2006CB705700-05 http://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of China 10527003 http://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of China 60672104 Research Fund for the Doctoral Program of Higher Education 20040001003 Joint Research Foundation of Beijing Education Committee SYS100010401",
year = "2007",
doi = "10.1155/2007/65641",
language = "English",
volume = "2007",
journal = "International Journal of Biomedical Imaging",
issn = "1687-4188",
}