View publication | Laboratory of Mathematical Methods of Image Processing

Title	Two approaches for noise filtering in 3D medical CT-images
Publication type	Conference paper
Author(s)	M.V. Storozhilova, A.S. Lukin, D.V. Yurin, V.E. Sinitsyn
Publication date	2012
Conference	22-th International Conference on Computer Graphics GraphiCon'2012
Page(s)	68-72
Address	Moscow, Russia
Abstract	Noise in 3D computer tomography (CT) images is close to white and becomes large when patient radiation doses are reduced. We propose two methods for noise reduction in CT images: 3D extension of fast rank algorithms (Rank-2.5D) and 3D extension of a non-local means algorithm (NLM-2.5D). We call both our algorithms ��2.5D�� because the 3-dimensional NLM algorithm is slightly asymmetric by slice axes, while our Rank algorithms, being fully symmetric mathematically and by results, have some implementation asymmetry. A comparison of the methods is presented. It is shown that NLM-2.5D method has the best quality, but is very computationally expensive: its complexity quickly rises as a function of the neighborhood size, while Rank-2.5D only shows a linear growth. Artificial test sequences are used for signal-to-noise performance measurements, while real CT scans are used for visual assessment of results.
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@INPROCEEDINGS{*,
  Title = {Two approaches for noise filtering in 3D medical CT-images},
  Author = {M. V. Storozhilova and A. S. Lukin and D. V. Yurin and V. E. Sinitsyn},
  BookTitle = {22-th International Conference on Computer Graphics GraphiCon'2012},
  Year = {2012},
  Pages = {68--72},
  Address = {Moscow, Russia},
  Language = {english}
}