Download PDF
Methods Inf Med 2010; 49(05): 542-546
DOI: 10.3414/ME09-02-0029
Special Topic – Original Articles
Schattauer GmbH

Signal Interpretation from Low-dosage Acquisition

An Investigation for Computed Tomographic Imaging
L. Cheng
1   Department of Engineering, Trinity College, Hartford, CT, USA
› Author Affiliations
Further Information

Publication History

received: 12 October 2009

accepted: 11 January 2010

Publication Date:
17 January 2018 (online)

    Permissions and Reprints

Summary

Objectives: This paper focuses on how we could analyze and interpret filtered back-projection reconstructed signals from low-dose computed tomographic (CT) imaging systems. There exists a growing imbalance between dosage reduction and effective signal interpretation. At the same time, low-dose applications are undergoing alarming growth.

Methods: This paper interprets filtered back-projection images in low-dose CT systems and details the possible properties of the artifacts. The interpretation leads to design of a new multi-image filtered back-projection approach that allows artifacts to be effectively identified across multiple images. We use this approach as a building block to propose a new reconstruction method that enables effective artifacts reduction and efficient implementation.

Results: Experiments with both clinical and simulated low-dose images demonstrate the validity and effectiveness of the proposed approach.

Conclusions: This study discusses a new FBP-based reconstruction approach based on signal interpretation from low-dosage acquisition. This method uses multiple filtered back-projection images from projection subsets to provide clues for distinguishing underlying clinical structure from artifacts. A framework is derived for effective signal interpretation and artifacts reduction. It requires no hardware change and a minimum amount of extra software support compared with current CT systems. Clinical and simulated low-dose CT scans demonstrated effectiveness of the proposed method.

Keywords

Image reconstruction - computed tomography
 

  • References

  • 1 Kak A, Slaney M. Principles of Computerized Tomographic Imaging. IEEE Press; 1988
    Google Scholar
  • 2 Jain A. Fundamentals of Digital Image Processing. Prentice Hall; 1989
    Google Scholar
  • 3 Herman G. Image Reconstruction from Projections: The Fundamentals of Computerized Tomography. New York: Academic Press; 1980
    Google Scholar
  • 4 Deans R. The Radon Transform and some of its applications. John Wiley & Sons; 1986
    Google Scholar
  • 5 Chan TF, Mulet P. Iterative methods for total variation image restoration. SIAM Journal on Numerical Analysis 1999
    PubMedGoogle Scholar
  • 6 Fornberg B, Herbst B. Tomographic Image Reconstruction, APPM 4380. University of Colorado at Boulder; 2000
    Google Scholar
  • 7 Alvino C, Yezzi A. Tomographic Reconstruction of Piecewise Smooth Images. Computer Vision and Pattern Recognition 2004; 1: 576-581.
    PubMedGoogle Scholar
  • 8 Tomasi C, Manduchi R. Bilateral filtering for gray and color images. Sixth International Conference on Computer Vision, New Delhi, India: 1998. pp 839-846.
    Google Scholar
  • 9 Manglos S, Gange G, Krol A, Thomas F, Narayanaswamy R. Transmission maximum-likelihood reconstruction with ordered subsets for cone beam CT. Phys Med Biol 1995; 40: 1225-1241.
    CrossrefPubMedGoogle Scholar
  • 10 DeMan B, Nuyts J, Dupont P, Marchal G, Suetens P. Reduction of metal artifacts in X-ray computed tomography using a transmission maximum a posteriori algorithm. IEEE Trans Nucl Sci 2000; 47: 977-981.
    CrossrefPubMedGoogle Scholar