Multivariate snr in spectral computed tomography

Jayasai R. Rajagopal; Faraz Farhadi; Ayele H. Negussie; Ehsan Abadi; Pooyan Sahbaee; Babak Saboury; Ashkan A. Malayeri; William F. Pritchard; Elizabeth C. Jones; Ehsan Samei

doi:10.1117/12.2581079

Multivariate snr in spectral computed tomography

Jayasai R. Rajagopal, Faraz Farhadi, Ayele H. Negussie, Ehsan Abadi, Pooyan Sahbaee, Babak Saboury, Ashkan A. Malayeri, William F. Pritchard, Elizabeth C. Jones, Ehsan Samei

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

1 Scopus citations

Abstract

In this work, we define a theoretical approach to characterizing the signal-to-noise ratio (SNR) of multi-channeled systems such as spectral computed tomography image series. Spectral image datasets encompass multiple near-simultaneous acquisitions that share information. The conventional definition of SNR is applicable to a single image and thus does not account for the interaction of information between images in a series. We propose an extension of the conventional SNR definition into a multivariate space where each image in the series is treated as a separate information channel thus defining a spectral SNR matrix. We apply this to the specific case of contrast-to-noise ratio (CNR). This matrix is able to account for the conventional CNR of each image in the series as well as a covariance weighted CNR (Cov-CNR), which accounts for the covariance between two images in the series. We evaluate this experimentally with data from an investigational photon-counting CT scanner (Siemens).

Original language	English
Title of host publication	Medical Imaging 2021
Subtitle of host publication	Physics of Medical Imaging
Editors	Hilde Bosmans, Wei Zhao, Lifeng Yu
Publisher	SPIE
ISBN (Electronic)	9781510640191
DOIs	https://doi.org/10.1117/12.2581079
State	Published - 2021
Externally published	Yes
Event	Medical Imaging 2021: Physics of Medical Imaging - Virtual, Online, United States Duration: Feb 15 2021 → Feb 19 2021

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	11595
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2021: Physics of Medical Imaging
Country/Territory	United States
City	Virtual, Online
Period	02/15/21 → 02/19/21

Funding

This study was supported by the National Institutes of Health (NIH) Clinical Center Radiology and Imaging Sciences (RADIS), the National Institute of Biomedical Imaging and Bioengineering (NIBIB) (R01 EB001838) and the NIH Intramural Research Program (NIH Z01 1ZID BC011242, and CL040015). The NIH and Siemens Medical Solutions have a Cooperative Research and Development Agreement providing financial and material support including the photon-counting CT system. The content of this manuscript does not necessarily reflect the views or policies of the Department of Health and Human Services, nor do mention of trade names, commercial products, or organizations imply endorsement by the United States Government.

Funders	Funder number
National Institutes of Health
National Institute of Biomedical Imaging and Bioengineering	Z01 1ZID BC011242, R01 EB001838, CL040015

Keywords

Computed tomography
Image quality
Metric
Photon counting

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10.1117/12.2581079

Cite this

Rajagopal, J. R., Farhadi, F., Negussie, A. H., Abadi, E., Sahbaee, P., Saboury, B., Malayeri, A. A., Pritchard, W. F., Jones, E. C., & Samei, E. (2021). Multivariate snr in spectral computed tomography. In H. Bosmans, W. Zhao, & L. Yu (Eds.), Medical Imaging 2021: Physics of Medical Imaging Article 115954I (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11595). SPIE. https://doi.org/10.1117/12.2581079

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abstract = "In this work, we define a theoretical approach to characterizing the signal-to-noise ratio (SNR) of multi-channeled systems such as spectral computed tomography image series. Spectral image datasets encompass multiple near-simultaneous acquisitions that share information. The conventional definition of SNR is applicable to a single image and thus does not account for the interaction of information between images in a series. We propose an extension of the conventional SNR definition into a multivariate space where each image in the series is treated as a separate information channel thus defining a spectral SNR matrix. We apply this to the specific case of contrast-to-noise ratio (CNR). This matrix is able to account for the conventional CNR of each image in the series as well as a covariance weighted CNR (Cov-CNR), which accounts for the covariance between two images in the series. We evaluate this experimentally with data from an investigational photon-counting CT scanner (Siemens).",

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author = "Rajagopal, {Jayasai R.} and Faraz Farhadi and Negussie, {Ayele H.} and Ehsan Abadi and Pooyan Sahbaee and Babak Saboury and Malayeri, {Ashkan A.} and Pritchard, {William F.} and Jones, {Elizabeth C.} and Ehsan Samei",

note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Medical Imaging 2021: Physics of Medical Imaging ; Conference date: 15-02-2021 Through 19-02-2021",

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doi = "10.1117/12.2581079",

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Rajagopal, JR, Farhadi, F, Negussie, AH, Abadi, E, Sahbaee, P, Saboury, B, Malayeri, AA, Pritchard, WF, Jones, EC & Samei, E 2021, Multivariate snr in spectral computed tomography. in H Bosmans, W Zhao & L Yu (eds), Medical Imaging 2021: Physics of Medical Imaging., 115954I, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11595, SPIE, Medical Imaging 2021: Physics of Medical Imaging, Virtual, Online, United States, 02/15/21. https://doi.org/10.1117/12.2581079

Multivariate snr in spectral computed tomography. / Rajagopal, Jayasai R.; Farhadi, Faraz; Negussie, Ayele H. et al.
Medical Imaging 2021: Physics of Medical Imaging. ed. / Hilde Bosmans; Wei Zhao; Lifeng Yu. SPIE, 2021. 115954I (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11595).

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

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AU - Farhadi, Faraz

AU - Negussie, Ayele H.

AU - Abadi, Ehsan

AU - Sahbaee, Pooyan

AU - Saboury, Babak

AU - Malayeri, Ashkan A.

AU - Pritchard, William F.

AU - Jones, Elizabeth C.

AU - Samei, Ehsan

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N2 - In this work, we define a theoretical approach to characterizing the signal-to-noise ratio (SNR) of multi-channeled systems such as spectral computed tomography image series. Spectral image datasets encompass multiple near-simultaneous acquisitions that share information. The conventional definition of SNR is applicable to a single image and thus does not account for the interaction of information between images in a series. We propose an extension of the conventional SNR definition into a multivariate space where each image in the series is treated as a separate information channel thus defining a spectral SNR matrix. We apply this to the specific case of contrast-to-noise ratio (CNR). This matrix is able to account for the conventional CNR of each image in the series as well as a covariance weighted CNR (Cov-CNR), which accounts for the covariance between two images in the series. We evaluate this experimentally with data from an investigational photon-counting CT scanner (Siemens).

AB - In this work, we define a theoretical approach to characterizing the signal-to-noise ratio (SNR) of multi-channeled systems such as spectral computed tomography image series. Spectral image datasets encompass multiple near-simultaneous acquisitions that share information. The conventional definition of SNR is applicable to a single image and thus does not account for the interaction of information between images in a series. We propose an extension of the conventional SNR definition into a multivariate space where each image in the series is treated as a separate information channel thus defining a spectral SNR matrix. We apply this to the specific case of contrast-to-noise ratio (CNR). This matrix is able to account for the conventional CNR of each image in the series as well as a covariance weighted CNR (Cov-CNR), which accounts for the covariance between two images in the series. We evaluate this experimentally with data from an investigational photon-counting CT scanner (Siemens).

KW - Computed tomography

KW - Image quality

KW - Metric

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BT - Medical Imaging 2021

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PB - SPIE

T2 - Medical Imaging 2021: Physics of Medical Imaging

Y2 - 15 February 2021 through 19 February 2021

ER -

Multivariate snr in spectral computed tomography

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