Approximation of voxel-level variances from spatial-variances for single scan PET data

P. J. Markiewicz; J. C. Matthews; A. J. Reader

doi:10.1109/NSSMIC.2012.6551922

Approximation of voxel-level variances from spatial-variances for single scan PET data

P. J. Markiewicz, J. C. Matthews, A. J. Reader

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

Abstract

Variance is one of the important metrics which is very useful in characterizing PET images, in particular when used in parameter estimation of dynamic PET data and in comparing different reconstruction algorithms or correction methods. © 2012 IEEE.

Original language	English
Title of host publication	IEEE Nuclear Science Symposium Conference Record\|IEEE Nucl. Sci. Symp. Conf. Rec.
Pages	4032-4035
Number of pages	3
DOIs	https://doi.org/10.1109/NSSMIC.2012.6551922
Publication status	Published - 2012
Event	2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012 - Anaheim, CA Duration: 1 Jul 2012 → … http://<Go to ISI>://WOS:000326814203033

Conference

Conference	2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012
City	Anaheim, CA
Period	1/07/12 → …
Internet address	http://<Go to ISI>://WOS:000326814203033

Keywords

Monte Carlo methods
brain
image reconstruction
iterative methods
medical image processing
phantoms
positron emission tomography
statistical analysis
Monte Carlo method
OSEM
bootstrap method
correction method
iterative reconstruction algorithm
ordered subset expectation maximization
raclopride
single human brain phantom scan
single scan PET data
voxel-level variance estimation
voxel-level variance-standard deviation

Access to Document

10.1109/NSSMIC.2012.6551922

Cite this

@inproceedings{297256c152fa4889beb3a48eadafbab3,

title = "Approximation of voxel-level variances from spatial-variances for single scan PET data",

abstract = "Variance is one of the important metrics which is very useful in characterizing PET images, in particular when used in parameter estimation of dynamic PET data and in comparing different reconstruction algorithms or correction methods. {\textcopyright} 2012 IEEE.",

keywords = "Monte Carlo methods, brain, image reconstruction, iterative methods, medical image processing, phantoms, positron emission tomography, statistical analysis, Monte Carlo method, OSEM, bootstrap method, correction method, iterative reconstruction algorithm, ordered subset expectation maximization, raclopride, single human brain phantom scan, single scan PET data, voxel-level variance estimation, voxel-level variance-standard deviation",

author = "Markiewicz, {P. J.} and Matthews, {J. C.} and Reader, {A. J.}",

year = "2012",

doi = "10.1109/NSSMIC.2012.6551922",

language = "English",

isbn = "9781467320306",

pages = "4032--4035",

booktitle = "IEEE Nuclear Science Symposium Conference Record|IEEE Nucl. Sci. Symp. Conf. Rec.",

note = "2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012 ; Conference date: 01-07-2012",

url = "http://<Go to ISI>://WOS:000326814203033",

}

Markiewicz, PJ, Matthews, JC & Reader, AJ 2012, Approximation of voxel-level variances from spatial-variances for single scan PET data. in IEEE Nuclear Science Symposium Conference Record|IEEE Nucl. Sci. Symp. Conf. Rec.. pp. 4032-4035, 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012, Anaheim, CA, 1/07/12. https://doi.org/10.1109/NSSMIC.2012.6551922

TY - GEN

T1 - Approximation of voxel-level variances from spatial-variances for single scan PET data

AU - Markiewicz, P. J.

AU - Matthews, J. C.

AU - Reader, A. J.

PY - 2012

Y1 - 2012

N2 - Variance is one of the important metrics which is very useful in characterizing PET images, in particular when used in parameter estimation of dynamic PET data and in comparing different reconstruction algorithms or correction methods. © 2012 IEEE.

AB - Variance is one of the important metrics which is very useful in characterizing PET images, in particular when used in parameter estimation of dynamic PET data and in comparing different reconstruction algorithms or correction methods. © 2012 IEEE.

KW - Monte Carlo methods

KW - brain

KW - image reconstruction

KW - iterative methods

KW - medical image processing

KW - phantoms

KW - positron emission tomography

KW - statistical analysis

KW - Monte Carlo method

KW - OSEM

KW - bootstrap method

KW - correction method

KW - iterative reconstruction algorithm

KW - ordered subset expectation maximization

KW - raclopride

KW - single human brain phantom scan

KW - single scan PET data

KW - voxel-level variance estimation

KW - voxel-level variance-standard deviation

U2 - 10.1109/NSSMIC.2012.6551922

DO - 10.1109/NSSMIC.2012.6551922

M3 - Conference contribution

SN - 9781467320306

SP - 4032

EP - 4035

BT - IEEE Nuclear Science Symposium Conference Record|IEEE Nucl. Sci. Symp. Conf. Rec.

T2 - 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012

Y2 - 1 July 2012

ER -

Approximation of voxel-level variances from spatial-variances for single scan PET data

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this