Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System

Zahra Ashouri; Chad R. Hunter; Benjamin A. Spencer; Guobao Wang; Richard M. Dansereau; Robert A. Dekemp

doi:10.1109/EMBC.2019.8856752

Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System

Zahra Ashouri, Chad R. Hunter, Benjamin A. Spencer, Guobao Wang, Richard M. Dansereau, Robert A. Dekemp

Radiology

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

1 Scopus citations

Abstract

Image reconstruction for positron emission tomography (PET) can be challenging and the resulting image typically has high noise. The kernel-based reconstruction method [1], incorporates prior anatomic information in the reconstruction algorithm to reduce noise while preserving resolution. Prior information is incorporated in the reconstruction algorithm by means of spatial kernels originally used in machine learning. In this paper, the kernel-based method is used to reconstruct PET images of sympathetic innervation in the heart. The resulting images are compared with standard Ordered Subset Expectation Maximization (OSEM) reconstructed images qualitatively and quantitatively using data from 6 human subjects. The kernel-based method demonstrated superior SNR with preserved contrast and accuracy compared to OSEM.

Original language	English (US)
Title of host publication	2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	832-835
Number of pages	4
ISBN (Electronic)	9781538613115
DOIs	https://doi.org/10.1109/EMBC.2019.8856752
State	Published - Jul 2019
Event	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany Duration: Jul 23 2019 → Jul 27 2019

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Country	Germany
City	Berlin
Period	7/23/19 → 7/27/19

Fingerprint

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Cite this

Ashouri, Z., Hunter, C. R., Spencer, B. A., Wang, G., Dansereau, R. M., & Dekemp, R. A. (2019). Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 (pp. 832-835). [8856752] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2019.8856752

Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System. / Ashouri, Zahra; Hunter, Chad R.; Spencer, Benjamin A.; Wang, Guobao; Dansereau, Richard M.; Dekemp, Robert A.

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 832-835 8856752 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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

Ashouri, Z, Hunter, CR, Spencer, BA, Wang, G, Dansereau, RM & Dekemp, RA 2019, Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System. in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8856752, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., pp. 832-835, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, 7/23/19. https://doi.org/10.1109/EMBC.2019.8856752

Ashouri Z, Hunter CR, Spencer BA, Wang G, Dansereau RM, Dekemp RA. Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 832-835. 8856752. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2019.8856752

Ashouri, Zahra ; Hunter, Chad R. ; Spencer, Benjamin A. ; Wang, Guobao ; Dansereau, Richard M. ; Dekemp, Robert A. / Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 832-835 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{dcfa0c5263a7432ab72788aefa6a8bed,

title = "Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System",

abstract = "Image reconstruction for positron emission tomography (PET) can be challenging and the resulting image typically has high noise. The kernel-based reconstruction method [1], incorporates prior anatomic information in the reconstruction algorithm to reduce noise while preserving resolution. Prior information is incorporated in the reconstruction algorithm by means of spatial kernels originally used in machine learning. In this paper, the kernel-based method is used to reconstruct PET images of sympathetic innervation in the heart. The resulting images are compared with standard Ordered Subset Expectation Maximization (OSEM) reconstructed images qualitatively and quantitatively using data from 6 human subjects. The kernel-based method demonstrated superior SNR with preserved contrast and accuracy compared to OSEM.",

author = "Zahra Ashouri and Hunter, {Chad R.} and Spencer, {Benjamin A.} and Guobao Wang and Dansereau, {Richard M.} and Dekemp, {Robert A.}",

year = "2019",

month = jul,

doi = "10.1109/EMBC.2019.8856752",

language = "English (US)",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "832--835",

booktitle = "2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019",

note = "41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 ; Conference date: 23-07-2019 Through 27-07-2019",

}

TY - GEN

T1 - Kernel-Based Reconstruction of C-11-Hydroxyephedrine Cardiac PET Images of the Sympathetic Nervous System

AU - Ashouri, Zahra

AU - Hunter, Chad R.

AU - Spencer, Benjamin A.

AU - Wang, Guobao

AU - Dansereau, Richard M.

AU - Dekemp, Robert A.

PY - 2019/7

Y1 - 2019/7

N2 - Image reconstruction for positron emission tomography (PET) can be challenging and the resulting image typically has high noise. The kernel-based reconstruction method [1], incorporates prior anatomic information in the reconstruction algorithm to reduce noise while preserving resolution. Prior information is incorporated in the reconstruction algorithm by means of spatial kernels originally used in machine learning. In this paper, the kernel-based method is used to reconstruct PET images of sympathetic innervation in the heart. The resulting images are compared with standard Ordered Subset Expectation Maximization (OSEM) reconstructed images qualitatively and quantitatively using data from 6 human subjects. The kernel-based method demonstrated superior SNR with preserved contrast and accuracy compared to OSEM.

AB - Image reconstruction for positron emission tomography (PET) can be challenging and the resulting image typically has high noise. The kernel-based reconstruction method [1], incorporates prior anatomic information in the reconstruction algorithm to reduce noise while preserving resolution. Prior information is incorporated in the reconstruction algorithm by means of spatial kernels originally used in machine learning. In this paper, the kernel-based method is used to reconstruct PET images of sympathetic innervation in the heart. The resulting images are compared with standard Ordered Subset Expectation Maximization (OSEM) reconstructed images qualitatively and quantitatively using data from 6 human subjects. The kernel-based method demonstrated superior SNR with preserved contrast and accuracy compared to OSEM.

UR - http://www.scopus.com/inward/record.url?scp=85077890711&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85077890711&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2019.8856752

DO - 10.1109/EMBC.2019.8856752

M3 - Conference contribution

C2 - 31946024

AN - SCOPUS:85077890711

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 832

EP - 835

BT - 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

Y2 - 23 July 2019 through 27 July 2019

ER -

Access to Document

10.1109/EMBC.2019.8856752