Anatomy-guided brain pet imaging incorporating a joint prior model

Lijun Lu; Jianhua Ma; Jing Tang; Qianjin Feng; Arman Rahmim; Wufan Chen

doi:10.1109/isbi.2014.6868031

Anatomy-guided brain pet imaging incorporating a joint prior model

Lijun Lu, Jianhua Ma, Jing Tang, Qianjin Feng, Arman Rahmim, Wufan Chen

School of Medicine

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

2 Scopus citations

Abstract

We proposed a maximum a posterior (MAP) framework for incorporating information from co-registered anatomical images into PET image reconstruction through a novel anato-functional joint prior. The characteristic of the utilized hyperbolic potential function is determinate by the voxel intensity differences within the anatomical image, while the penalization is computed based on voxel intensity differences in reconstructed PET images. Using realistic simulated short time ¹⁸FDG PET scan data, we optimized the performance of the proposed MAP reconstruction with the joint prior (JP-MAP), and compared its performance with conventional 3D maximum likelihood expectation maximization (MLEM) and MAP reconstructions. The proposed JP-MAP reconstruction algorithm resulted in quantitatively enhanced reconstructed images, as demonstrated in extensive ¹⁸FDG PET simulation study.

Original language	English (US)
Title of host publication	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	959-962
Number of pages	4
ISBN (Electronic)	9781467319591
DOIs	https://doi.org/10.1109/isbi.2014.6868031
State	Published - Jul 29 2014
Event	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China Duration: Apr 29 2014 → May 2 2014

Publication series

Name	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Other

Other	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/Territory	China
City	Beijing
Period	4/29/14 → 5/2/14

Keywords

Anatomical priors
Joint prior
Maximum a posterior
Positron emission tomography

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/isbi.2014.6868031

Cite this

Lu, L., Ma, J., Tang, J., Feng, Q., Rahmim, A., & Chen, W. (2014). Anatomy-guided brain pet imaging incorporating a joint prior model. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 959-962). Article 6868031 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/isbi.2014.6868031

Anatomy-guided brain pet imaging incorporating a joint prior model. / Lu, Lijun; Ma, Jianhua; Tang, Jing et al.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 959-962 6868031 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014).

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

Lu, L, Ma, J, Tang, J, Feng, Q, Rahmim, A & Chen, W 2014, Anatomy-guided brain pet imaging incorporating a joint prior model. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6868031, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 959-962, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China, 4/29/14. https://doi.org/10.1109/isbi.2014.6868031

Lu L, Ma J, Tang J, Feng Q, Rahmim A, Chen W. Anatomy-guided brain pet imaging incorporating a joint prior model. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 959-962. 6868031. (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). doi: 10.1109/isbi.2014.6868031

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abstract = "We proposed a maximum a posterior (MAP) framework for incorporating information from co-registered anatomical images into PET image reconstruction through a novel anato-functional joint prior. The characteristic of the utilized hyperbolic potential function is determinate by the voxel intensity differences within the anatomical image, while the penalization is computed based on voxel intensity differences in reconstructed PET images. Using realistic simulated short time 18FDG PET scan data, we optimized the performance of the proposed MAP reconstruction with the joint prior (JP-MAP), and compared its performance with conventional 3D maximum likelihood expectation maximization (MLEM) and MAP reconstructions. The proposed JP-MAP reconstruction algorithm resulted in quantitatively enhanced reconstructed images, as demonstrated in extensive 18FDG PET simulation study.",

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Anatomy-guided brain pet imaging incorporating a joint prior model

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Keywords

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