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Title: Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction

Abstract

Purpose: Dynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction. Methods: SIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects. Results: For SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS. Conclusion: The analysis supportsmore » the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.« less

Authors:
 [1];  [2];  [3];  [1];  [4];  [4];  [4];  [5]
  1. Florida Institute of Technology, Melbourne FL (United States). School of Computing
  2. Radiology and Cancer Imaging, Tampa, FL (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  4. Univ. of California, San Francisco, CA (United States). Dept. of Radiology and Biomedical Imaging, Physical Research Lab.
  5. Univ. of California, San Francisco, CA (United States). Dept. of Radiology and Biomedical Imaging, Physical Research Lab.; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1559152
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 45; Journal Issue: 10; Journal ID: ISSN 0094-2405
Publisher:
American Association of Physicists in Medicine
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Mitra, Debasis, Abdalah, Mahmoud, Boutchko, Rostyslav, Chang, Haoran, Shrestha, Uttam, Botvinick, Elias, Seo, Youngho, and Gullberg, Grant T. Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction. United States: N. p., 2018. Web. doi:10.1002/mp.13099.
Mitra, Debasis, Abdalah, Mahmoud, Boutchko, Rostyslav, Chang, Haoran, Shrestha, Uttam, Botvinick, Elias, Seo, Youngho, & Gullberg, Grant T. Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction. United States. doi:10.1002/mp.13099.
Mitra, Debasis, Abdalah, Mahmoud, Boutchko, Rostyslav, Chang, Haoran, Shrestha, Uttam, Botvinick, Elias, Seo, Youngho, and Gullberg, Grant T. Fri . "Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction". United States. doi:10.1002/mp.13099. https://www.osti.gov/servlets/purl/1559152.
@article{osti_1559152,
title = {Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction},
author = {Mitra, Debasis and Abdalah, Mahmoud and Boutchko, Rostyslav and Chang, Haoran and Shrestha, Uttam and Botvinick, Elias and Seo, Youngho and Gullberg, Grant T.},
abstractNote = {Purpose: Dynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction. Methods: SIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects. Results: For SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS. Conclusion: The analysis supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.},
doi = {10.1002/mp.13099},
journal = {Medical Physics},
number = 10,
volume = 45,
place = {United States},
year = {2018},
month = {8}
}

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