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  • Research Article
  • Open Access

A Self-Adaptive Approach for the Detection and Correction of Stripes in the Sinogram: Suppression of Ring Artifacts in CT Imaging

  • 1,
  • 2 and
  • 1, 2Email author
EURASIP Journal on Advances in Signal Processing20102011:183547

  • Received: 4 June 2010
  • Accepted: 14 August 2010
  • Published:


The digital X-ray detectors often generate stripe artifact in the sinogram which in turn creates ring artifact in the reconstructed micro-Computed Tomography ( -CT), C-Arm CT, and most recent dental CT images. Such ring artifacts not only obscure image details in the regions of interest but also mask the whole image with some artifacts. In this paper, novel techniques are proposed for the detection and suppression of ring artifacts in the sinogram domain. As ring artifacts are manifested as edge creating stripes, single or contiguous, in the sinogram, they are detected based on a set of specific conditions derived from the second derivative of the sinogram and a new self-adaptive threshold computed from its first derivative. A new method for the detection of wide band contiguous stripes using the mean curve and multilevel polyphase decomposition of the given sinogram is also proposed here. For the correction of ring artifacts, novel variable window moving average (VWMA) and weighted moving average (WMA) filters are proposed in this work. To evaluate and compare the performance of the proposed algorithm, various types of synthetic and real -CT images are used. Experimental results show that the proposed method can detect ring artifacts with high accuracy and thus remove them more effectively without imparting noticeable distortion in the image as compared to other reported techniques.


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Authors’ Affiliations

Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh
Department of Biomedical Engineering, Kyung Hee University, Kyungki, 446-701, Republic of Korea


© A. N. M. Ashrafuzzaman et al. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.