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An algorithm for noise correction of dual-energy computed tomography material density images

International Journal of Computer Assisted Radiology and Surgery volume 10, pages 87–100 (2015)Cite this article

Abstract

Purpose

Dual-energy computed tomography (DECT) images can undergo a two-material decomposition process which results in two images containing material density information. Material density images obtained by that process result in images with increased pixel noise. Noise reduction in those images is desirable in order to improve image quality.

Methods

A noise reduction algorithm for material density images was developed and tested. A three-level wavelet approach combined with the application of an anisotropic diffusion filter was used. During each level, the resulting noise maps are further processed, until the original resolution is reached and the final noise maps obtained. Our method works in image space and, therefore, can be applied to any type of material density images obtained from any DECT vendor. A quantitative evaluation of the noise-reduced images using the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and 2D noise power spectrum was done to quantify the improvements.

Results

The noise reduction algorithm was applied to a set of images resulting in images with higher SNR and CNR than the raw density images obtained by the decomposition process. The average improvement in terms of SNR gain was about 49 % while CNR gain was about 52 %. The difference between the raw and filtered regions of interest mean values was far from reaching statistical significance (minimum \(p> 0.89\), average \(p> 0.97\)).

Conclusion

We have demonstrated through a series of quantitative analyses that our novel noise reduction algorithm improves the image quality of DECT material density images.

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Conflict of interest

Rafael Simon Maia, Christian Jacob, Amy K. Hara, Alvin C. Silva, William Pavlicek and J.Ross Mitchell declare that they have no conflict of interest.

Ethical standards All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008.

Author information

Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Dr NW, Calgary, AB , T2N 1N4, Canada

    Rafael Simon Maia & Christian Jacob

  2. Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ , 85259, USA

    Amy K. Hara, Alvin C. Silva, William Pavlicek & Mitchell J. Ross

Authors
  1. Rafael Simon Maia
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  2. Christian Jacob
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  3. Amy K. Hara
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  4. Alvin C. Silva
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  5. William Pavlicek
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  6. Mitchell J. Ross
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Corresponding author

Correspondence to Rafael Simon Maia.

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Maia, R.S., Jacob, C., Hara, A.K. et al. An algorithm for noise correction of dual-energy computed tomography material density images. Int J CARS 10, 87–100 (2015). https://doi.org/10.1007/s11548-014-1006-z

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  • DOI: https://doi.org/10.1007/s11548-014-1006-z

Keywords

  • Material density
  • Dual-energy computed tomography
  • Noise reduction
  • Anisotropic diffusion