A two-stage human brain MRI segmentation scheme using fuzzy logic Conference Paper uri icon

abstract

  • 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.

name of conference

  • Proceedings of 1995 IEEE International Conference on Fuzzy Systems. The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium

published proceedings

  • Proceedings of 1995 IEEE International Conference on Fuzzy Systems. The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium

author list (cited authors)

  • Chang, C., Killman, G. R., Ying, H., Kent, T. A., & Yen, J.

citation count

  • 10

complete list of authors

  • Chang, Chih-Wei||Killman, GR||Ying, Hao||Kent, TA||Yen, J

publication date

  • January 1995