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

15 February 2021 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

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Proceedings Volume 11595, Medical Imaging 2021: Physics of Medical Imaging; 115954I (2021) https://doi.org/10.1117/12.2581079
Event: SPIE Medical Imaging, 2021, Online Only

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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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Jayasai R. Rajagopal, Faraz Farhadi, Ayele H. Negussie, Ehsan Abadi, Pooyan Sahbaee, Babak Saboury, Ashkan A. Malayeri, William F. Pritchard, Elizabeth C. Jones, and Ehsan Samei "Multivariate SNR in spectral computed tomography", Proc. SPIE 11595, Medical Imaging 2021: Physics of Medical Imaging, 115954I (15 February 2021); https://doi.org/10.1117/12.2581079

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