Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography

Guobao Wang; Changqing Li; Simon R Cherry; Jinyi Qi

doi:10.1109/ISBI.2011.5872451

Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography

Guobao Wang, Changqing Li, Simon R Cherry, Jinyi Qi

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

3 Scopus citations

Abstract

We have developed a hybrid system for imaging small animals using fluorescence optical tomography (FOT) and positron emission tomography (PET) simultaneously. This paper presents a statistical method for reconstructing spatial distribution of dual-labeled tracers from the combined PET and FOT data. We use the Poisson likelihood function for the PET data and Gaussian distribution for the FOT data. The log-posterior density function is maximized by an optimization transfer algorithm. Computer simulations show that the hybrid reconstruction using combined PET-FOT data can achieve a better bias versus standard deviation performance than reconstructions using either PET or FOT data alone.

Original language	English (US)
Title of host publication	Proceedings - International Symposium on Biomedical Imaging
Pages	488-491
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2011.5872451
State	Published - 2011
Event	2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States Duration: Mar 30 2011 → Apr 2 2011

Other

Other	2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
Country/Territory	United States
City	Chicago, IL
Period	3/30/11 → 4/2/11

Keywords

fluorescence optical tomography
image reconstruction
Positron emission tomography

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI.2011.5872451

Cite this

Wang, G, Li, C, Cherry, SR & Qi, J 2011, Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography. in Proceedings - International Symposium on Biomedical Imaging., 5872451, pp. 488-491, 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11, Chicago, IL, United States, 3/30/11. https://doi.org/10.1109/ISBI.2011.5872451

@inproceedings{8ea0741c37494198a4ce3fcb464a72e2,

title = "Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography",

abstract = "We have developed a hybrid system for imaging small animals using fluorescence optical tomography (FOT) and positron emission tomography (PET) simultaneously. This paper presents a statistical method for reconstructing spatial distribution of dual-labeled tracers from the combined PET and FOT data. We use the Poisson likelihood function for the PET data and Gaussian distribution for the FOT data. The log-posterior density function is maximized by an optimization transfer algorithm. Computer simulations show that the hybrid reconstruction using combined PET-FOT data can achieve a better bias versus standard deviation performance than reconstructions using either PET or FOT data alone.",

keywords = "fluorescence optical tomography, image reconstruction, Positron emission tomography",

author = "Guobao Wang and Changqing Li and Cherry, {Simon R} and Jinyi Qi",

year = "2011",

doi = "10.1109/ISBI.2011.5872451",

language = "English (US)",

isbn = "9781424441280",

pages = "488--491",

booktitle = "Proceedings - International Symposium on Biomedical Imaging",

note = "2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 ; Conference date: 30-03-2011 Through 02-04-2011",

}

TY - GEN

T1 - Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography

AU - Wang, Guobao

AU - Li, Changqing

AU - Cherry, Simon R

AU - Qi, Jinyi

PY - 2011

Y1 - 2011

N2 - We have developed a hybrid system for imaging small animals using fluorescence optical tomography (FOT) and positron emission tomography (PET) simultaneously. This paper presents a statistical method for reconstructing spatial distribution of dual-labeled tracers from the combined PET and FOT data. We use the Poisson likelihood function for the PET data and Gaussian distribution for the FOT data. The log-posterior density function is maximized by an optimization transfer algorithm. Computer simulations show that the hybrid reconstruction using combined PET-FOT data can achieve a better bias versus standard deviation performance than reconstructions using either PET or FOT data alone.

AB - We have developed a hybrid system for imaging small animals using fluorescence optical tomography (FOT) and positron emission tomography (PET) simultaneously. This paper presents a statistical method for reconstructing spatial distribution of dual-labeled tracers from the combined PET and FOT data. We use the Poisson likelihood function for the PET data and Gaussian distribution for the FOT data. The log-posterior density function is maximized by an optimization transfer algorithm. Computer simulations show that the hybrid reconstruction using combined PET-FOT data can achieve a better bias versus standard deviation performance than reconstructions using either PET or FOT data alone.

KW - fluorescence optical tomography

KW - image reconstruction

KW - Positron emission tomography

UR - http://www.scopus.com/inward/record.url?scp=80055061269&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80055061269&partnerID=8YFLogxK

U2 - 10.1109/ISBI.2011.5872451

DO - 10.1109/ISBI.2011.5872451

M3 - Conference contribution

AN - SCOPUS:80055061269

SN - 9781424441280

SP - 488

EP - 491

BT - Proceedings - International Symposium on Biomedical Imaging

T2 - 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11

Y2 - 30 March 2011 through 2 April 2011

ER -

Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this