SVD investigation of modeling scatter in multiple energy windows for improved SPECT images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work singular value decomposition (SVD) techniques are used to investigate how the use of low energy photons and multiple energy windows affects the noise properties of SPECT reconstructions. We have previously shown that, when modeling scatter in the projector of iterative reconstruction algorithms, simultaneous reconstruction from multiple energy window data can result in very different noise characteristics. Further, the properties depend upon the width and number of energy windows used. To investigate this further, we have generated photon transport matrices for an elliptical phantom and a number of energy window schemes. Transfer matrices were also generated for the cases of perfect scatter rejection, and ideal scatter subtraction. These matrices were decomposed using SVD, and the signal and noise power spectra were computed using the projection eigenvector basis. Results indicate very different noise properties for the various energy window combinations. The perfect scatter rejection case resulted in the lowest noise power; and modeling scatter in a 20% window performed slightly better than the scatter subtraction case. When including lower energies, forming a contiguous series of seven small energy windows outperformed a single large energy window, but neither method achieved a lower noise power than the standard 20% window. Finally, one combination of windows is presented which utilizes low energy scattered photons and achieves a lower noise power than the standard 20% energy window.

Original languageEnglish (US)
Title of host publicationIEEE Nuclear Science Symposium & Medical Imaging Conference
PublisherIEEE
Pages1097-1101
Number of pages5
Volume2
StatePublished - 1995
Externally publishedYes
EventProceedings of the 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference. Part 1 (of 3) - San Francisco, CA, USA
Duration: Oct 21 1995Oct 28 1995

Other

OtherProceedings of the 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference. Part 1 (of 3)
CitySan Francisco, CA, USA
Period10/21/9510/28/95

Fingerprint

Singular value decomposition
Photons
Power spectrum
Eigenvalues and eigenfunctions

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Kadrmas, D. J., Frey, E. C., & Tsui, B. M. W. (1995). SVD investigation of modeling scatter in multiple energy windows for improved SPECT images. In IEEE Nuclear Science Symposium & Medical Imaging Conference (Vol. 2, pp. 1097-1101). IEEE.

SVD investigation of modeling scatter in multiple energy windows for improved SPECT images. / Kadrmas, Dan J.; Frey, Eric C.; Tsui, Benjamin M W.

IEEE Nuclear Science Symposium & Medical Imaging Conference. Vol. 2 IEEE, 1995. p. 1097-1101.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kadrmas, DJ, Frey, EC & Tsui, BMW 1995, SVD investigation of modeling scatter in multiple energy windows for improved SPECT images. in IEEE Nuclear Science Symposium & Medical Imaging Conference. vol. 2, IEEE, pp. 1097-1101, Proceedings of the 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference. Part 1 (of 3), San Francisco, CA, USA, 10/21/95.
Kadrmas DJ, Frey EC, Tsui BMW. SVD investigation of modeling scatter in multiple energy windows for improved SPECT images. In IEEE Nuclear Science Symposium & Medical Imaging Conference. Vol. 2. IEEE. 1995. p. 1097-1101
Kadrmas, Dan J. ; Frey, Eric C. ; Tsui, Benjamin M W. / SVD investigation of modeling scatter in multiple energy windows for improved SPECT images. IEEE Nuclear Science Symposium & Medical Imaging Conference. Vol. 2 IEEE, 1995. pp. 1097-1101
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abstract = "In this work singular value decomposition (SVD) techniques are used to investigate how the use of low energy photons and multiple energy windows affects the noise properties of SPECT reconstructions. We have previously shown that, when modeling scatter in the projector of iterative reconstruction algorithms, simultaneous reconstruction from multiple energy window data can result in very different noise characteristics. Further, the properties depend upon the width and number of energy windows used. To investigate this further, we have generated photon transport matrices for an elliptical phantom and a number of energy window schemes. Transfer matrices were also generated for the cases of perfect scatter rejection, and ideal scatter subtraction. These matrices were decomposed using SVD, and the signal and noise power spectra were computed using the projection eigenvector basis. Results indicate very different noise properties for the various energy window combinations. The perfect scatter rejection case resulted in the lowest noise power; and modeling scatter in a 20{\%} window performed slightly better than the scatter subtraction case. When including lower energies, forming a contiguous series of seven small energy windows outperformed a single large energy window, but neither method achieved a lower noise power than the standard 20{\%} window. Finally, one combination of windows is presented which utilizes low energy scattered photons and achieves a lower noise power than the standard 20{\%} energy window.",
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