TY - GEN
T1 - Ultra-high resolution photon-counting detector CT reconstruction using spectral prior image constrained compressed-sensing (UHR-SPICCS)
AU - Rajendran, Kishore
AU - Tao, Shengzhen
AU - Abdurakhimova, Dilbar
AU - Leng, Shuai
AU - McCollough, Cynthia
N1 - Funding Information:
This research was supported in part by NIH Grant, R01-EB016966 and C06-RR018898. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The research photon-counting CT system described herein is not commercially available.
Publisher Copyright:
© 2018 SPIE.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Photon-counting detectors
KW - compressed sensing
KW - computed tomography
KW - image reconstruction
KW - multi-energy
KW - prior image constrained compressed sensing
KW - ultra-high resolution
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U2 - 10.1117/12.2294628
DO - 10.1117/12.2294628
M3 - Conference contribution
AN - SCOPUS:85049253077
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2018
A2 - Schmidt, Taly Gilat
A2 - Chen, Guang-Hong
A2 - Lo, Joseph Y.
PB - SPIE
T2 - Medical Imaging 2018: Physics of Medical Imaging
Y2 - 12 February 2018 through 15 February 2018
ER -