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Proceedings Paper

Cone-beam x-ray luminescence computed tomography reconstruction from single-view based on total variance
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Paper Abstract

As an emerging hybrid imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed based on the development of X-ray excitable nanoparticles. Fast three-dimensional (3-D) CB-XLCT imaging has attracted significant attention for the application of XLCT in fast dynamic imaging study. Currently, due to the short data collection time, single-view CB-XLCT imaging achieves fast resolving the three-dimensional (3-D) distribution of X-ray-excitable nanoparticles. However, owing to only one angle projection data is used in the reconstruction, the single-view CB-XLCT inverse problem is inherently ill-conditioned, which makes image reconstruction highly susceptible to the effects of noise and numerical errors. To solve the ill-posed inverse problem, using the sparseness of the X-ray-excitable nanoparticles distribution as the prior, a new reconstruction approach based on total variance is proposed in this study. To evaluate the performance of the proposed approach, a phantom experiment was performed based on a CB-XLCT imaging system. The experiments indicate that the reconstruction from single-view XCLT can provide satisfactory results based on the proposed approach. In conclusion, with the reconstruction approach based on total variance, we implement a fast XLCT reconstruction of high quality with only one angle projection data used, which would be helpful for fast dynamic imaging study. In future, we will focus on how to applying the proposed TV-based reconstruction method and CB-XLCT imaging system to image fast biological distributions of the X-ray excitable nanophosphors in vivo.

Paper Details

Date Published: 9 March 2018
PDF: 6 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 1057336 (9 March 2018); doi: 10.1117/12.2293221
Show Author Affiliations
Tianshuai Liu, Fourth Military Medical Univ. (China)
Junyan Rong, Fourth Military Medical Univ. (China)
Peng Gao, Fourth Military Medical Univ. (China)
Zhengrong Liang, The State Univ. of New York (United States)
Wenli Zhang, Fourth Military Medical Univ. (China)
Yuanke Zhang, Fourth Military Medical Univ. (China)
Hongbing Lu, Fourth Military Medical Univ. (China)


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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