Nonlocal means-based regularizations for statistical CT reconstruction

Hao Zhang, Jianhua Ma, Yan Liu, Hao Han, Lihong Li, Jing Wang, Zhengrong Liang

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

8 Scopus citations

Abstract

Statistical iterative reconstruction (SIR) methods have shown remarkable gains over the conventional filtered backprojection (FBP) method in improving image quality for low-dose computed tomography (CT). They reconstruct the CT images by maximizing/minimizing a cost function in a statistical sense, where the cost function usually consists of two terms: the data-fidelity term modeling the statistics of measured data, and the regularization term reflecting a prior information. The regularization term in SIR plays a critical role for successful image reconstruction, and an established family of regularizations is based on the Markov random field (MRF) model. Inspired by the success of nonlocal means (NLM) algorithm in image processing applications, we proposed, in this work, a family of generic and edgepreserving NLM-based regularizations for SIR. We evaluated one of them where the potential function takes the quadratic-form. Experimental results with both digital and physical phantoms clearly demonstrated that SIR with the proposed regularization can achieve more significant gains than SIR with the widely-used Gaussian MRF regularization and the conventional FBP method, in terms of image noise reduction and resolution preservation.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2014
Subtitle of host publicationPhysics of Medical Imaging
PublisherSPIE
ISBN (Print)9780819498267
DOIs
StatePublished - Jan 1 2014
EventMedical Imaging 2014: Physics of Medical Imaging - San Diego, CA, United States
Duration: Feb 17 2014Feb 20 2014

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9033
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2014: Physics of Medical Imaging
CountryUnited States
CitySan Diego, CA
Period2/17/142/20/14

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Keywords

  • CT reconstruction
  • non-local means
  • regularizations
  • shifted Poisson approximation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Zhang, H., Ma, J., Liu, Y., Han, H., Li, L., Wang, J., & Liang, Z. (2014). Nonlocal means-based regularizations for statistical CT reconstruction. In Medical Imaging 2014: Physics of Medical Imaging [903337] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9033). SPIE. https://doi.org/10.1117/12.2043949