Debasis Mitra1, Mahmoud Abdalah2, Rostyslav Boutchko3, Haoran Chang1, Uttam Shrestha4, Elias Botvinick4, Youngho Seo4, Grant T Gullberg3,4. 1. School of Computing, Florida Institute of Technology, 150 West University Blvd., Melbourne, FL, 32901, USA. 2. Radiology and Cancer Imaging, 12902 USF Magnolia Drive, Tampa, FL, 33612, USA. 3. Molecular Biophys. & Integ. Bio., Lawrence Berkeley National Lab, MS 55R0121, Berkeley, CA, 94720, USA. 4. Physics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143-0946, USA.
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 supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.
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.
Authors: Maria Sciammarella; Uttam M Shrestha; Youngho Seo; Grant T Gullberg; Elias H Botvinick Journal: J Nucl Cardiol Date: 2017-08-03 Impact factor: 5.952
Authors: Celeste D Winant; Carina Mari Aparici; Yuval R Zelnik; Bryan W Reutter; Arkadiusz Sitek; Stephen L Bacharach; Grant T Gullberg Journal: Phys Med Biol Date: 2011-12-14 Impact factor: 3.609
Authors: Simona Ben-Haim; Venkatesh L Murthy; Christopher Breault; Rayjanah Allie; Arkadiusz Sitek; Nathaniel Roth; Jolene Fantony; Stephen C Moore; Mi-Ae Park; Marie Kijewski; Athar Haroon; Piotr Slomka; Kjell Erlandsson; Rafael Baavour; Yoel Zilberstien; Jamshed Bomanji; Marcelo F Di Carli Journal: J Nucl Med Date: 2013-04-11 Impact factor: 10.057