Imagewise model fitting for generating parametric images in dynamic PET studies

Sung-Cheng Huang; Yun Zhou; David Stout; Jorge R. Barrio

doi:10.1117/12.312564

3 July 1998 Imagewise model fitting for generating parametric images in dynamic PET studies

Sung-Cheng Huang, Yun Zhou, David Stout, Jorge R. Barrio

Proceedings Volume 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images; (1998) https://doi.org/10.1117/12.312564
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

In this study, we explore the use of non-linear regression for model fitting of PET measured kinetics on a pixel-by-pixel basis for generating parametric images of micro-parameters of kinetic models. We evaluate quantitatively the noise propagation of two regression methods using computer simulated data, and examine the feasibility of generating parametric images for two different real PET studies -- a human FDG study and a monkey FDOPA study. The results demonstrated that general image-wise model fitting is practically feasible for dynamic PET studies.

Citation Download Citation

Sung-Cheng Huang, Yun Zhou, David Stout, and Jorge R. Barrio "Imagewise model fitting for generating parametric images in dynamic PET studies", Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); https://doi.org/10.1117/12.312564

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