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Proceedings Paper

Ultra-high resolution photon-counting detector CT reconstruction using spectral prior image constrained compressed-sensing (UHR-SPICCS)
Author(s): Kishore Rajendran; Shengzhen Tao; Dilbar Abdurakhimova; Shuai Leng; Cynthia McCollough
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Paper Abstract

Photon-counting detector based CT (PCD-CT) enables dose efficient high resolution imaging, in addition to providing multi-energy information. This allows better delineation of anatomical structures crucial for several clinical applications ranging from temporal bone imaging to pulmonary nodule visualization. Due to the smaller detector pixel sizes required for high resolution imaging, the PCD-CT images suffer from higher noise levels. The image quality is further degraded in narrow energy bins as a consequence of low photon counts. This limits the potential benefits that high-resolution PCD-CT could offer. Conventional reconstruction techniques such as the filtered back projection (FBP) have poor performance when reconstructing noisy CT projection data. To enable low noise multi-energy reconstructions, we employed a spectral prior image constrained compressed sensing (SPICCS) framework that exploits the spatio-spectral redundancy in the multi-energy acquisitions. We demonstrated noise reduction in narrow energy bins without losing energy-specific attenuation information and spatial resolution. We scanned an anthropomorphic head phantom, and a euthanized pig using our whole-body prototype PCD-CT system in the ultra-high resolution mode at 120 kV. Image reconstructions were performed using SPICCS and compared with conventional FBP. Noise reduction of 18 to 46% was noticed in narrow energy bins corresponding to 25 − 65 keV and 65 − 120 keV, while the mean CT number was preserved. Spatial resolution measurement showed similar modulation transfer function (MTF) values between FBP and SPICCS, demonstrating preservation of spatial resolution.

Paper Details

Date Published: 9 March 2018
PDF: 6 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 1057318 (9 March 2018); doi: 10.1117/12.2294628
Show Author Affiliations
Kishore Rajendran, Mayo Clinic (United States)
Shengzhen Tao, Mayo Clinic (United States)
Dilbar Abdurakhimova, Mayo Clinic (United States)
Shuai Leng, Mayo Clinic (United States)
Cynthia McCollough, Mayo Clinic (United States)

Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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