Statistical image reconstruction for low-dose dual energy CT using alpha-divergence constrained spectral redundancy information

Dong Zeng, Zhaoying Bian, Jing Huang, Yuting Liao, Jing Wang, Zhengrong Liang, Jianhua Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Dual energy computed tomography (DECT) has flu-proved capability of differentiating different materials compared to conventional CT. However, due to non-negligible radiation exposure to patients, dose reduction has recently become a critical concern in CT imaging field. Moreover, direct material decomposition techniques such as numerical inversion can yield significantly amplified noise in the basic material images, and this is another common tissue in DECT imaging. In this work, to address the two issues, we present an iterative algorithm. More specifically, the DECT images are reconstructed by minimizing one objective function consisting a data-fidelity term using Alpha-divergence to describe the statistical distribution of the DE sinogram data and a regularization term utilizing redundant information within DECT images. For simplicity, the present algorithm is termed as "AlphaD-aviNLM". To minimize the associative objective function, a modified proximal forward-backward splitting algorithm is proposed. Digital phantom was utilized to validate and evaluate the present AlphaD-aviNLM algorithm. The experimental results characterize the performance of the present AlphaD-aviNLM algorithm.

Original languageEnglish (US)
Title of host publication2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509016426
DOIs
StatePublished - Oct 16 2017
Event2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016 - Strasbourg, France
Duration: Oct 29 2016Nov 6 2016

Publication series

Name2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
Volume2017-January

Other

Other2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
CountryFrance
CityStrasbourg
Period10/29/1611/6/16

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Instrumentation
  • Nuclear and High Energy Physics
  • Electronic, Optical and Magnetic Materials

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    Zeng, D., Bian, Z., Huang, J., Liao, Y., Wang, J., Liang, Z., & Ma, J. (2017). Statistical image reconstruction for low-dose dual energy CT using alpha-divergence constrained spectral redundancy information. In 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016 [8069590] (2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2016.8069590