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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Sparse-View CT Image Recovery Using Two-Step Iterative Shrinkage-Thresholding Algorithm

  • Chae, Byung Gyu (IT Convergence Technology Research Laboratory, ETRI) ;
  • Lee, Sooyeul (IT Convergence Technology Research Laboratory, ETRI)
  • Received : 2015.05.07
  • Accepted : 2015.10.29
  • Published : 2015.12.01
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Abstract

We investigate an image recovery method for sparse-view computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other first-order methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm -sing measured projection data.

Keywords

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