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 Citations (Scopus)

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.

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
PublisherIEEE
Pages649-654
Number of pages6
Volume2
StatePublished - 1995
EventProceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn
Duration: Mar 20 1995Mar 24 1995

Other

OtherProceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5)
CityYokohama, Jpn
Period3/20/953/24/95

Fingerprint

Magnetic resonance imaging
Fuzzy Logic
Fuzzy logic
Brain
Segmentation
Pixels
Fuzzy systems
Pixel
Fuzzy Systems
Cerebrospinal fluid
Classify
Knowledge based systems
Fuzzy rules
Image segmentation
Fuzzy Rule-based Systems
Fuzzy C-means Algorithm
Image Segmentation
Assign
Observer
Initial conditions

All Science Journal Classification (ASJC) codes

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

Cite this

Chang, C. W., Hillman, G. R., Ying, H., Kent, T. A., & Yen, J. (1995). Two-stage human brain MRI segmentation scheme using fuzzy logic. In Anon (Ed.), International Joint Conference on the 4th IEEE International Conference on Fuzzy Systems and the 2nd International Fuzzy Engineering Symposium (Vol. 2, pp. 649-654). IEEE.
Chang, Chih Wei ; Hillman, Gilbert R. ; Ying, Hao ; Kent, Thomas A. ; Yen, John. / Two-stage human brain MRI segmentation scheme using fuzzy logic. International Joint Conference on the 4th IEEE International Conference on Fuzzy Systems and the 2nd International Fuzzy Engineering Symposium. editor / Anon. Vol. 2 IEEE, 1995. pp. 649-654
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title = "Two-stage human brain MRI segmentation scheme using fuzzy logic",
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.",
author = "Chang, {Chih Wei} and Hillman, {Gilbert R.} and Hao Ying and Kent, {Thomas A.} and John Yen",
year = "1995",
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Chang, CW, Hillman, GR, Ying, H, Kent, TA & Yen, J 1995, Two-stage human brain MRI segmentation scheme using fuzzy logic. in Anon (ed.), International Joint Conference on the 4th IEEE International Conference on Fuzzy Systems and the 2nd International Fuzzy Engineering Symposium. vol. 2, IEEE, pp. 649-654, Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5), Yokohama, Jpn, 3/20/95.

Two-stage human brain MRI segmentation scheme using fuzzy logic. / Chang, Chih Wei; Hillman, Gilbert R.; Ying, Hao; Kent, Thomas A.; Yen, John.

International Joint Conference on the 4th IEEE International Conference on Fuzzy Systems and the 2nd International Fuzzy Engineering Symposium. ed. / Anon. Vol. 2 IEEE, 1995. p. 649-654.

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

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T1 - Two-stage human brain MRI segmentation scheme using fuzzy logic

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N2 - 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.

AB - 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.

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Chang CW, Hillman GR, Ying H, Kent TA, Yen J. Two-stage human brain MRI segmentation scheme using fuzzy logic. In Anon, editor, International Joint Conference on the 4th IEEE International Conference on Fuzzy Systems and the 2nd International Fuzzy Engineering Symposium. Vol. 2. IEEE. 1995. p. 649-654