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Implementation of penalized-likelihood statistical reconstruction for polychromatic dual-energy CT

  • Qiong Xu
  • , Xuanqin Mou
  • , Shaojie Tang
  • , Hong Wei
  • , Zhang Yizhai
  • , Tao Luo
  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

This paper presents a statistical reconstruction algorithm for dual-energy (DE) CT of polychromatic x-ray source. Each pixel in the imaged object is assumed to be composed of two basis materials (i.e., bone and soft tissue) and a penalizedlikelihood objective function is developed to determine the densities of the two basis materials. Two penalty terms are used respectively to penalize the bone density difference and the soft tissue density difference in neighboring pixels. A gradient ascent algorithm for monochromatic objective function is modified to maximize the polychromatic penalizedlikelihood objective function using the convexity technique. In order to reduce computation consumption, the denominator of the update step is pre-calculated with reasonable approximation replacements. Ordered-subsets method is applied to speed up the iteration. Computer simulation is implemented to evaluate the penalized-likelihood algorithm. The results indicate that this statistical method yields the best quality.

Original languageEnglish
Title of host publicationMedical Imaging 2009
Subtitle of host publicationPhysics of Medical Imaging
DOIs
StatePublished - 2009
EventMedical Imaging 2009: Physics of Medical Imaging - Lake Buena Vista, FL, United States
Duration: 9 Feb 200912 Feb 2009

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7258
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2009: Physics of Medical Imaging
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period9/02/0912/02/09

Keywords

  • Dual-energy CT
  • Penalized-likelihood
  • Polychromatic
  • Statistical image reconstruction

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