Improved intensity inhomogeneity correction techniques in MR brain image segmentation

Laszlo Szilagyi, Laszlo David, Sandor Miklos Szilagyi, Balazs Benyo, Zoltan Benyo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a pre-filtering technique for Gaussian and impulse noise elimination, and a smoothening filter that assists the fuzzy c-means (FCM) algorithm at the estimation of inhomogeneity as a slowly varying additive or multiplicative noise. The segmentation is produced by FCM algorithm together with the INU estimation. The slowly varying behaviour of the bias or gain field is assured by a smoothening filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show, that the proposed method provides accurate segmentation. The produced segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.

Original languageEnglish
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Edition1 PART 1
DOIs
Publication statusPublished - Dec 1 2008
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of
Duration: Jul 6 2008Jul 11 2008

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume17
ISSN (Print)1474-6670

Other

Other17th World Congress, International Federation of Automatic Control, IFAC
CountryKorea, Republic of
CitySeoul
Period7/6/087/11/08

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Keywords

  • Biomedical imaging systems
  • Biomedical system modeling, simulation and visualization

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Szilagyi, L., David, L., Szilagyi, S. M., Benyo, B., & Benyo, Z. (2008). Improved intensity inhomogeneity correction techniques in MR brain image segmentation. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC (1 PART 1 ed.). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 17, No. 1 PART 1). https://doi.org/10.3182/20080706-5-KR-1001.3749