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Spectrum optimization in photon counting detector based iodine K-edge CT imaging
Author(s): Mang Feng; Xu Ji; Kevin Treb; Ran Zhang; Guang-Hong Chen; Ke Li
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Paper Abstract

Iodine K-edge CT imaging utilizes the sudden increase in the attenuation coefficient of iodine when the x-ray energy exceeds the K-shell binding energy of iodine. Early works on K-edge CT used multiple K-edge filters to generate different quasi-monoenergetic spectra with mean energies that straddled the iodine K-edge, and then multiple projections acquired with these spectra were processed to enhance the sensitivity of imaging iodine. Recent developments in energy-resolving photon counting detector (PCD) technology offer the potential for single-shot K-edge CT imaging. However, the performance of PCD-based iodine K-edge CT is often limited by the relatively low energy of the iodine K-edge (33.2 keV) compared with the mean energy of a polychromatic spectrum used in CT. This work explored the potential of introducing an iodine beam filter to PCD-based iodine K-edge CT to improve its imaging performance. To optimize the beam filtration condition, a realistic energy response function of an experimental PCD system was used when calculating the Cramér-Rao Lower Bounds (CRLBs) of three-material (iodine, bone, and water) decomposition estimators for each filtration condition. Experimental studies with a benchtop PCD CT system were performed to confirm the CRLB results. Both theoretical and experimental results demonstrated that by using an optimized iodine filter, quantitative accuracy of material basis images was improved. Compared with a commercial dual-energy-CT system, the optimized experimental K-edge CT system effectively reduced residual iodine signal in the bone basis image and reduced residual bone signal in the water-basis image.

Paper Details

Date Published: 7 March 2019
PDF: 6 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109481C (7 March 2019); doi: 10.1117/12.2512893
Show Author Affiliations
Mang Feng, Univ. of Wisconsin-Madison (United States)
Xu Ji, Univ. of Wisconsin-Madison (United States)
Kevin Treb, Univ. of Wisconsin-Madison (United States)
Ran Zhang, Univ. of Wisconsin-Madison (United States)
Guang-Hong Chen, Univ. of Wisconsin-Madison (United States)
Ke Li, Univ. of Wisconsin-Madison (United States)


Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

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