Local response prediction in model-based CT material decomposition

Wenying Wang; Steven Tilley; Matthew Tivnan; J. Webster Stayman

doi:10.1117/12.2534437

Local response prediction in model-based CT material decomposition

Wenying Wang, Steven Tilley, Matthew Tivnan, J. Webster Stayman

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

3 Scopus citations

Abstract

Spectral CT is an emerging modality that permits material decomposition and density estimation through the use of energy-dependent information in measurements. Direct model-based material decomposition algorithms have been developed that incorporate statistical models and advanced regularization schemes to improve density estimates and lower exposure requirements. However, understanding and control of the relationship between regularization and image properties is complex with interactions between spectral channels and material bases. In particular, regularization in one material basis can affect the image properties of other material bases, and vice versa. In this work, we derived a closed-form set of local impulse responses for the solutions to a general, regularized, model-based material decomposition (MBMD) objective. These predictors quantify both the spatial resolution in each material image as well as the influence of regularization of one material basis on other material images. This information can be used prospectively to tune regularization parameters for specific imaging goals.

Original language	English (US)
Title of host publication	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Editors	Samuel Matej, Scott D. Metzler
Publisher	SPIE
ISBN (Electronic)	9781510628373
DOIs	https://doi.org/10.1117/12.2534437
State	Published - 2019
Externally published	Yes
Event	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019 - Philadelphia, United States Duration: Jun 2 2019 → Jun 6 2019

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11072
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019
Country/Territory	United States
City	Philadelphia
Period	6/2/19 → 6/6/19

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.2534437

Cite this

Wang, W., Tilley, S., Tivnan, M., & Stayman, J. W. (2019). Local response prediction in model-based CT material decomposition. In S. Matej, & S. D. Metzler (Eds.), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine Article 110720Z (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072). SPIE. https://doi.org/10.1117/12.2534437

Local response prediction in model-based CT material decomposition. / Wang, Wenying; Tilley, Steven; Tivnan, Matthew et al.
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. ed. / Samuel Matej; Scott D. Metzler. SPIE, 2019. 110720Z (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072).

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

Wang, W, Tilley, S, Tivnan, M & Stayman, JW 2019, Local response prediction in model-based CT material decomposition. in S Matej & SD Metzler (eds), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine., 110720Z, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11072, SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019, Philadelphia, United States, 6/2/19. https://doi.org/10.1117/12.2534437

Wang W, Tilley S, Tivnan M, Stayman JW. Local response prediction in model-based CT material decomposition. In Matej S, Metzler SD, editors, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. SPIE. 2019. 110720Z. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2534437

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abstract = "Spectral CT is an emerging modality that permits material decomposition and density estimation through the use of energy-dependent information in measurements. Direct model-based material decomposition algorithms have been developed that incorporate statistical models and advanced regularization schemes to improve density estimates and lower exposure requirements. However, understanding and control of the relationship between regularization and image properties is complex with interactions between spectral channels and material bases. In particular, regularization in one material basis can affect the image properties of other material bases, and vice versa. In this work, we derived a closed-form set of local impulse responses for the solutions to a general, regularized, model-based material decomposition (MBMD) objective. These predictors quantify both the spatial resolution in each material image as well as the influence of regularization of one material basis on other material images. This information can be used prospectively to tune regularization parameters for specific imaging goals.",

author = "Wenying Wang and Steven Tilley and Matthew Tivnan and Stayman, {J. Webster}",

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AB - Spectral CT is an emerging modality that permits material decomposition and density estimation through the use of energy-dependent information in measurements. Direct model-based material decomposition algorithms have been developed that incorporate statistical models and advanced regularization schemes to improve density estimates and lower exposure requirements. However, understanding and control of the relationship between regularization and image properties is complex with interactions between spectral channels and material bases. In particular, regularization in one material basis can affect the image properties of other material bases, and vice versa. In this work, we derived a closed-form set of local impulse responses for the solutions to a general, regularized, model-based material decomposition (MBMD) objective. These predictors quantify both the spatial resolution in each material image as well as the influence of regularization of one material basis on other material images. This information can be used prospectively to tune regularization parameters for specific imaging goals.

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Local response prediction in model-based CT material decomposition

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