Segmentation of rat brain MR images using a hybrid fuzzy system

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

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

3 Citations (Scopus)

Abstract

We have developed a magnetic resonance (MR) image segmentation system which consists of a fuzzy ruled-based system and a fuzzy c-means algorithm (FCM). The first stage of the system is the fuzzy ruled-based system which classifies most pixels of MR images into several known classes and one `unclassified' class. In the second stage, the classified result of the first stage is used to find the initial prototypes for FCM and the `unclassified' pixels are classified by FCM. The result of this combination is a very robust classification system. Rat brain MR images with stroke lesions are segmented. This system successfully identified the penumbra area of the rat brain.

Original languageEnglish (US)
Title of host publicationProc 1994 1 Int Jt Conf NAFIPS IFIS NASA
EditorsLarry Hall, Hao Ying, Reza Langari, John Yen
PublisherIEEE
Pages55-59
Number of pages5
StatePublished - 1994
EventProceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA - San Antonio, TX, USA
Duration: Dec 18 1994Dec 21 1994

Other

OtherProceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA
CitySan Antonio, TX, USA
Period12/18/9412/21/94

Fingerprint

Fuzzy systems
Magnetic resonance
Rats
Brain
Pixels
Image segmentation

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Chang, C. W., Hillman, G. R., Ying, H., Kent, T. A., & Yen, J. (1994). Segmentation of rat brain MR images using a hybrid fuzzy system. In L. Hall, H. Ying, R. Langari, & J. Yen (Eds.), Proc 1994 1 Int Jt Conf NAFIPS IFIS NASA (pp. 55-59). IEEE.
Chang, Chih Wei ; Hillman, Gilbert R. ; Ying, Hao ; Kent, Thomas A. ; Yen, John. / Segmentation of rat brain MR images using a hybrid fuzzy system. Proc 1994 1 Int Jt Conf NAFIPS IFIS NASA. editor / Larry Hall ; Hao Ying ; Reza Langari ; John Yen. IEEE, 1994. pp. 55-59
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title = "Segmentation of rat brain MR images using a hybrid fuzzy system",
abstract = "We have developed a magnetic resonance (MR) image segmentation system which consists of a fuzzy ruled-based system and a fuzzy c-means algorithm (FCM). The first stage of the system is the fuzzy ruled-based system which classifies most pixels of MR images into several known classes and one `unclassified' class. In the second stage, the classified result of the first stage is used to find the initial prototypes for FCM and the `unclassified' pixels are classified by FCM. The result of this combination is a very robust classification system. Rat brain MR images with stroke lesions are segmented. This system successfully identified the penumbra area of the rat brain.",
author = "Chang, {Chih Wei} and Hillman, {Gilbert R.} and Hao Ying and Kent, {Thomas A.} and John Yen",
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Chang, CW, Hillman, GR, Ying, H, Kent, TA & Yen, J 1994, Segmentation of rat brain MR images using a hybrid fuzzy system. in L Hall, H Ying, R Langari & J Yen (eds), Proc 1994 1 Int Jt Conf NAFIPS IFIS NASA. IEEE, pp. 55-59, Proceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA, San Antonio, TX, USA, 12/18/94.

Segmentation of rat brain MR images using a hybrid fuzzy system. / Chang, Chih Wei; Hillman, Gilbert R.; Ying, Hao; Kent, Thomas A.; Yen, John.

Proc 1994 1 Int Jt Conf NAFIPS IFIS NASA. ed. / Larry Hall; Hao Ying; Reza Langari; John Yen. IEEE, 1994. p. 55-59.

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

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T1 - Segmentation of rat brain MR images using a hybrid fuzzy system

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N2 - We have developed a magnetic resonance (MR) image segmentation system which consists of a fuzzy ruled-based system and a fuzzy c-means algorithm (FCM). The first stage of the system is the fuzzy ruled-based system which classifies most pixels of MR images into several known classes and one `unclassified' class. In the second stage, the classified result of the first stage is used to find the initial prototypes for FCM and the `unclassified' pixels are classified by FCM. The result of this combination is a very robust classification system. Rat brain MR images with stroke lesions are segmented. This system successfully identified the penumbra area of the rat brain.

AB - We have developed a magnetic resonance (MR) image segmentation system which consists of a fuzzy ruled-based system and a fuzzy c-means algorithm (FCM). The first stage of the system is the fuzzy ruled-based system which classifies most pixels of MR images into several known classes and one `unclassified' class. In the second stage, the classified result of the first stage is used to find the initial prototypes for FCM and the `unclassified' pixels are classified by FCM. The result of this combination is a very robust classification system. Rat brain MR images with stroke lesions are segmented. This system successfully identified the penumbra area of the rat brain.

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Chang CW, Hillman GR, Ying H, Kent TA, Yen J. Segmentation of rat brain MR images using a hybrid fuzzy system. In Hall L, Ying H, Langari R, Yen J, editors, Proc 1994 1 Int Jt Conf NAFIPS IFIS NASA. IEEE. 1994. p. 55-59