Denoising 3D Computed Tomography Images using New Modified Coherence Enhancing Diffusion Model

Feriel Romdhane, Faouzi Benzarti, Hamid Amiri

2016

Abstract

The denoising step for Computed Tomography (CT) images is an important challenge in the medical image processing. These images are degraded by low resolution and noise. In this paper, we propose a new method for 3D CT denoising based on Coherence Enhancing Diffusion model. Quantitative measures such as PSNR, SSIM and RMSE are computed to a phantom CT image in order to improve the efficiently of our proposed model, compared to a number of denoising algorithms. Furthermore, experimental results on a real 3D CT data show that this approach is effective and promising in removing noise and preserving details.

References

  1. Bakker, P., Van Vliet, L.J., Verbeek, P.W., 2001. Confidence and curvature estimation of curvilinear structures in 3-D. Proceedings of the 8th ICCV. Vancuver, Canada.
  2. Frangakis, A. and Hegerl, R., 2001. Noise reduction in electron tomographic reconstruction using nonlinear anisotropic diffusion. Journal of Structural Biology.
  3. Kroon, D.J., Slump, C.H., Maal, T., 2010. Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-beam CT. Medical Image Computing and Computer-Assistant Intervention, MICCAI.
  4. Magnier, B., Huanyu, X. and Montesinos, P., 2013. Half Gaussian Kernels Based Shock Filter for Image Deblurring and Regularization. 8th International Conference on Computer Vision, Imaging and Computer Graphic Therory and Application. France.
  5. Meijering, E., Niessen, W., Weickert, J. and Viergever, M., 2002. Diffusion-Enhanced Visualization and Quantification of Vascular Anomalies in ThreeDimensional Rotational Angiography: Results of an In-Vitro Evaluation. Medical Image Analysis.
  6. Mendrik, A., Vonken, E., Rutten, A., Viergever, M., Van Ginneken, B., 2009. Noise Reduction in Computed Tomography Scans using 3D Anisotropic Hybrid Diffusion with Continuous Switch. IEEE Trans. Med. Imaging.
  7. Perona, P., Malik, J., 1990. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Transactions on Pattern Analysis and Machine Intelligence.
  8. Pop, S., Lavialle, O., Terebes, R., Borda, M., 2007. A New Partial Differential Equation-Based Approach for 3D Data Denoising and Edge Preserving. TechnElectrotechn. et Energ. Bucarest.
  9. Romdhane, F., Benzarti, F., and Amiri, H., 2014. 3D Medical Images Denoising. In 1st International Image Processing Applications and Systems, Tunisia.
  10. Tschumperlé, D. 2006. Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE's. International Journal of Computer Vision.
  11. Van Kempen, G.M.P., Van, den Brink, N., Van Vliet, L.J., Van Ginkel, M., Verbeek, P.W., Blonk, H., 1999. The application of a local dimensionality estimator to the analysis of 3D microscopic network structures. Scandinavian Conference on Image Analysis. Greenland.
  12. Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E., 2004. Image quality assessment: form error visibility to structural similarity. IEEE Transactions on Image Processing.
  13. Weickert, J., 1999. Coherence-enhancing diffusion filtering. International Journal Computer vision.
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Paper Citation


in Harvard Style

Romdhane F., Benzarti F. and Amiri H. (2016). Denoising 3D Computed Tomography Images using New Modified Coherence Enhancing Diffusion Model . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 101-105. DOI: 10.5220/0005692701010105


in Bibtex Style

@conference{visapp16,
author={Feriel Romdhane and Faouzi Benzarti and Hamid Amiri},
title={Denoising 3D Computed Tomography Images using New Modified Coherence Enhancing Diffusion Model},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={101-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005692701010105},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Denoising 3D Computed Tomography Images using New Modified Coherence Enhancing Diffusion Model
SN - 978-989-758-175-5
AU - Romdhane F.
AU - Benzarti F.
AU - Amiri H.
PY - 2016
SP - 101
EP - 105
DO - 10.5220/0005692701010105