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Nonmonotone total variation minimization based projection restoration for low-dose CT reconstruction

  • Shan Shan Qian
  • , Jing Huang
  • , Jian Hua Ma
  • , Hua Zhang
  • , Nan Liu
  • , Xi Le Zhang
  • , Qian Jin Feng
  • , Wu Fan Chen
  • Southern Medical University

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In order to improve the reconstruction quality of low-dose CT image, a new approach is proposed based on low-dose CT projection restoration in this paper. First, projection data is transformed from Poisson distribution to Gaussian distribution using nonlinear Anscombe transform. Then, the Anscombe transformed data is filtered by an efficient nonmonotone total variation minimization denoising algorithm. Last, the reconstruction is achieved by inverse Anscombe transform and filtered back projection (FBP) method. Simulated and clinical low-dose CT data experimental results demonstrate that a high-quality CT image can be reconstructed.

Original languageEnglish
Pages (from-to)1702-1707
Number of pages6
JournalTien Tzu Hsueh Pao/Acta Electronica Sinica
Volume39
Issue number7
StatePublished - Jul 2011
Externally publishedYes

Keywords

  • Anscombe transform
  • Low-dose CT
  • Nonmonotone total variation
  • Projection restoration

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