A modified fuzzy c-means algorithm for MR brain image segmentation

László Szilágyi, Sándor M. Szilágyi, Z. Benyó

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

30 Citations (Scopus)

Abstract

Automated brain MR image segmentation is a challenging pattern recognition problem that received significant attention lately. The most popular solutions involve fuzzy c-means (FCM) or similar clustering mechanisms. Several improvements have been made to the standard FCM algorithm, in order to reduce its sensitivity to Gaussian, impulse, and intensity non-uniformity noises. This paper presents a modified FCM-based method that targets accurate and fast segmentation in case of mixed noises. The proposed method extracts a scalar feature value from the neighborhood of each pixel, using a context dependent filtering technique that deals with both spatial and gray level distances. These features are clustered afterwards by the histogram-based approach of the enhanced FCM algorithm. Results were evaluated based on synthetic phantoms and real MR images. Test experiments revealed that the proposed method provides better results compared to other reported FCM-based techniques. The achieved segmentation and the obtained fuzzy membership values represent excellent support for deformable contour model based cortical surface reconstruction methods.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages866-877
Number of pages12
Volume4633 LNCS
Publication statusPublished - 2007
Event4th International Conference on Image Analysis and Recognition, ICIAR 2007 - Montreal, Canada
Duration: Aug 22 2007Aug 24 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4633 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Conference on Image Analysis and Recognition, ICIAR 2007
CountryCanada
CityMontreal
Period8/22/078/24/07

Fingerprint

Fuzzy C-means Algorithm
Image segmentation
Image Segmentation
Fuzzy C-means
Brain
Surface reconstruction
Pattern recognition
Noise
Segmentation
Pixels
Fuzzy Membership
Surface Reconstruction
Non-uniformity
Phantom
Impulse
Histogram
Pattern Recognition
Cluster Analysis
Filtering
Pixel

Keywords

  • Context dependent filter
  • Feature extraction
  • Fuzzy c-means algorithm
  • Image segmentation
  • Magnetic resonance imaging
  • Noise elimination

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Szilágyi, L., Szilágyi, S. M., & Benyó, Z. (2007). A modified fuzzy c-means algorithm for MR brain image segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4633 LNCS, pp. 866-877). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4633 LNCS).

A modified fuzzy c-means algorithm for MR brain image segmentation. / Szilágyi, László; Szilágyi, Sándor M.; Benyó, Z.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4633 LNCS 2007. p. 866-877 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4633 LNCS).

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

Szilágyi, L, Szilágyi, SM & Benyó, Z 2007, A modified fuzzy c-means algorithm for MR brain image segmentation. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4633 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4633 LNCS, pp. 866-877, 4th International Conference on Image Analysis and Recognition, ICIAR 2007, Montreal, Canada, 8/22/07.
Szilágyi L, Szilágyi SM, Benyó Z. A modified fuzzy c-means algorithm for MR brain image segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4633 LNCS. 2007. p. 866-877. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Szilágyi, László ; Szilágyi, Sándor M. ; Benyó, Z. / A modified fuzzy c-means algorithm for MR brain image segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4633 LNCS 2007. pp. 866-877 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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