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Article
Sparse X-Ray CT Image Reconstruction Using ECME Hard Thresholding Methods
AIP Conference Proceedings
  • Kun Qiu, Iowa State University
  • Aleksandar Dogandžić, Iowa State University
Document Type
Conference Proceeding
Publication Date
1-1-2011
DOI
10.1063/1.3591889
Abstract

We apply expectation‐conditional maximization either (ECME) hard thresholding algorithms to X‐ray computed tomography (CT) reconstruction, where we implement the sampling operator using the nonuniform fast Fourier transform (NUFFT). The measurements follow an underdetermined linear model, where the regression‐coefficient vector is a sum of an unknown deterministic sparse signal component and a zero‐mean white Gaussian component with an unknown variance. Our ECME schemes aim at maximizing this model’s likelihood function with respect to the sparse signal and variance of the random signal component. These schemes exploit signal sparsity in the discrete wavelet transform (DWT) domain and yield better reconstructions than the traditional filtered backprojection (FBP) approach, which is demonstrated via numerical examples. In contrast with FBP, our methods achieve artifact‐free reconstructions in undersampled and limited‐angle projection examples. We also compare the ECME schemes with a state‐of‐the‐art convex sparse signal reconstruction approach in terms of the reconstruction speed.

Comments

The following article appeared in AIP Conference Proceedings 1335 (2011): 469 and may be found at doi:10.1063/1.3591889.

Rights
Copyright 2011 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.
Copyright Owner
American Institute of Physics
Language
en
Date Available
2014-10-08
File Format
application/pdf
Citation Information
Kun Qiu and Aleksandar Dogandžić. "Sparse X-Ray CT Image Reconstruction Using ECME Hard Thresholding Methods" AIP Conference Proceedings Vol. 1335 (2011) p. 469 - 476
Available at: http://works.bepress.com/aleksandar_dogandzic/21/