Image-wise 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

Image-wise model fitting for generating parametric images in dynamic PET studies

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	E.A. Hoffman
Pages	198-202
Number of pages	5
Volume	3337
DOIs	https://doi.org/10.1117/12.312564
State	Published - 1998
Externally published	Yes
Event	Medical Imaging 1998: Physiology and Function from Multidimensional Images - San Diego, CA, United States Duration: Feb 22 1998 → Feb 23 1998

Other

Other	Medical Imaging 1998: Physiology and Function from Multidimensional Images
Country/Territory	United States
City	San Diego, CA
Period	2/22/98 → 2/23/98

Keywords

[F-18]-L-DOPA (FDOPA)
[F-18]Fluorodeoxyglucose (FDG)
Biological information
Computer simulation
Dynamics
Model fitting
Non-linear regression
Nuclear medicine
Parametric image
Positron emission tomography (PET)

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

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10.1117/12.312564

Cite this

Huang, SC, Zhou, Y, Stout, D & Barrio, JR 1998, Image-wise model fitting for generating parametric images in dynamic PET studies. in EA Hoffman (ed.), Proceedings of SPIE - The International Society for Optical Engineering. vol. 3337, pp. 198-202, Medical Imaging 1998: Physiology and Function from Multidimensional Images, San Diego, CA, United States, 2/22/98. https://doi.org/10.1117/12.312564

@inproceedings{336856654377463bad293cdbe847e2e5,

title = "Image-wise model fitting for generating parametric images in dynamic PET studies",

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.",

keywords = "[F-18]-L-DOPA (FDOPA), [F-18]Fluorodeoxyglucose (FDG), Biological information, Computer simulation, Dynamics, Model fitting, Non-linear regression, Nuclear medicine, Parametric image, Positron emission tomography (PET)",

author = "Huang, {Sung Cheng} and Yun Zhou and David Stout and Barrio, {Jorge R.}",

year = "1998",

doi = "10.1117/12.312564",

language = "English (US)",

volume = "3337",

pages = "198--202",

editor = "E.A. Hoffman",

booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

note = "Medical Imaging 1998: Physiology and Function from Multidimensional Images ; Conference date: 22-02-1998 Through 23-02-1998",

}

TY - GEN

T1 - Image-wise model fitting for generating parametric images in dynamic PET studies

AU - Huang, Sung Cheng

AU - Zhou, Yun

AU - Stout, David

AU - Barrio, Jorge R.

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

KW - [F-18]-L-DOPA (FDOPA)

KW - [F-18]Fluorodeoxyglucose (FDG)

KW - Biological information

KW - Computer simulation

KW - Dynamics

KW - Model fitting

KW - Non-linear regression

KW - Nuclear medicine

KW - Parametric image

KW - Positron emission tomography (PET)

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UR - http://www.scopus.com/inward/citedby.url?scp=0032402891&partnerID=8YFLogxK

U2 - 10.1117/12.312564

DO - 10.1117/12.312564

M3 - Conference contribution

AN - SCOPUS:0032402891

VL - 3337

SP - 198

EP - 202

BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Hoffman, E.A.

T2 - Medical Imaging 1998: Physiology and Function from Multidimensional Images

Y2 - 22 February 1998 through 23 February 1998

ER -

Image-wise model fitting for generating parametric images in dynamic PET studies

Abstract

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Keywords

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