• DocumentCode
    3703741
  • Title

    A fast and accurate dental micro-CT image denoising based on total variation modeling

  • Author

    Mojtaba Lashgari;Hossein Rabbani;Mahdi Shahmorad;Michael Swain

  • Author_Institution
    Biomedical Engineering Dept., Faculty of Advanced Medical Technology, Isfahan University of Medical Sciences, Isfahan, Iran
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Quantitative evaluation of mineral density of carious dental lesion is one of the major aims in cariology investigations particularly in the study of caries remineralization. Nowadays X-ray micro computed tomography (Micro-CT) is used as a well-known modality for this purpose. However, the produced Micro-CT images are affected by substantial noise. To address this issue, we propose a new approach for de-noising dental Micro-CT images based on total variation (TV) modeling. The idea of applying this method traces back to the structural features of a tooth, and almost non-textural nature of noise-free images. So, using TV we intend to separate texture from cartoon which results in major reduction of the noise in Micro-CT dental images. Our simulation results on a dataset of 51 teeth of size 1000×1000 showed that our method outperforms BM3D method, currently one of the state-of-the-art de-noising methods, in terms of Contrast-to-Noise Ratio (123.02±11.29 vs. 96.79±6.87) while Edge Preservation Indexes are the same.
  • Keywords
    "Noise reduction","Dentistry","TV","Indexes","Minerals","Teeth","Computed tomography"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Systems (SiPS), 2015 IEEE Workshop on
  • Type

    conf

  • DOI
    10.1109/SiPS.2015.7345032
  • Filename
    7345032