Two-stage human brain MRI segmentation scheme using fuzzy logic

Chih Wei Chang, Gilbert R. Hillman, Hao Ying, Thomas A. Kent, John Yen

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

6 Scopus citations


We have developed a two-stage image segmentation scheme using fuzzy logic. Based on the scheme, a two-stage fuzzy system has been built for segmenting human brain MR images. The first stage is a fuzzy rule-based system that assigns memberships to pixels, classifies the pixels that have only one high membership and calculates the initial conditions for the next stage. The second stage is the fuzzy c-means algorithm, which classifies the undetermined pixels. Preliminary segmentation of the human brain MR images shows the two-stage fuzzy system could accurately determine white matter, gray matter, cerebrospinal fluid and HIV + lesion. The results were visually confirmed by expert observers. The satisfactory results achieved in this paper suggest the feasibility of developing similar segmentation systems for other types of images and the possibility of extending the two-stage scheme to multiple-stage schemes.

Original languageEnglish (US)
Title of host publicationInternational Joint Conference on the 4th IEEE International Conference on Fuzzy Systems and the 2nd International Fuzzy Engineering Symposium
Editors Anon
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
StatePublished - 1995
EventProceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn
Duration: Mar 20 1995Mar 24 1995


OtherProceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5)
CityYokohama, Jpn

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics


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