Cascade algorithm combined Kohonen feature map with fuzzy C-means applied in MR brain image segmentation

Chung Chih Lin; Jeng Ren Duann; Hui Cheng Cheng; Jyh Horng Chen

doi:10.1109/IEMBS.1996.652717

Cascade algorithm combined Kohonen feature map with fuzzy C-means applied in MR brain image segmentation

Chung Chih Lin^*, Jeng Ren Duann, Hui Cheng Cheng, Jyh Horng Chen

^*Corresponding author for this work

Institute of Education

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this study, a cascade algorithm combined Kohonen feature map with FCM was applied to segment the MR brain images. The method we proposed was proved has better performance than FCM method usually used in image segmentation researches. Because the algorithm is unsupervised, it can reduce the errors caused by intraobserver and interobserver estimation. In this paper, we also utilized the MR images acquired by PAIR protocol to verify the result of the image segmentation.

Original language	English
Pages (from-to)	1079-1080
Number of pages	2
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	3
DOIs	https://doi.org/10.1109/IEMBS.1996.652717
State	Published - 1996
Event	Proceedings of the 1996 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 5) - Amsterdam, Neth Duration: 31 Oct 1996 → 3 Nov 1996

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10.1109/IEMBS.1996.652717

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@article{e6bbdd928e8c4ecb89cdb89f350dacea,

title = "Cascade algorithm combined Kohonen feature map with fuzzy C-means applied in MR brain image segmentation",

abstract = "In this study, a cascade algorithm combined Kohonen feature map with FCM was applied to segment the MR brain images. The method we proposed was proved has better performance than FCM method usually used in image segmentation researches. Because the algorithm is unsupervised, it can reduce the errors caused by intraobserver and interobserver estimation. In this paper, we also utilized the MR images acquired by PAIR protocol to verify the result of the image segmentation.",

author = "Lin, {Chung Chih} and Duann, {Jeng Ren} and Cheng, {Hui Cheng} and Chen, {Jyh Horng}",

year = "1996",

doi = "10.1109/IEMBS.1996.652717",

language = "English",

volume = "3",

pages = "1079--1080",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1996 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 5) ; Conference date: 31-10-1996 Through 03-11-1996",

}

Cascade algorithm combined Kohonen feature map with fuzzy C-means applied in MR brain image segmentation. / Lin, Chung Chih; Duann, Jeng Ren; Cheng, Hui Cheng et al.
In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 3, 1996, p. 1079-1080.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Cascade algorithm combined Kohonen feature map with fuzzy C-means applied in MR brain image segmentation

AU - Lin, Chung Chih

AU - Duann, Jeng Ren

AU - Cheng, Hui Cheng

AU - Chen, Jyh Horng

PY - 1996

Y1 - 1996

N2 - In this study, a cascade algorithm combined Kohonen feature map with FCM was applied to segment the MR brain images. The method we proposed was proved has better performance than FCM method usually used in image segmentation researches. Because the algorithm is unsupervised, it can reduce the errors caused by intraobserver and interobserver estimation. In this paper, we also utilized the MR images acquired by PAIR protocol to verify the result of the image segmentation.

AB - In this study, a cascade algorithm combined Kohonen feature map with FCM was applied to segment the MR brain images. The method we proposed was proved has better performance than FCM method usually used in image segmentation researches. Because the algorithm is unsupervised, it can reduce the errors caused by intraobserver and interobserver estimation. In this paper, we also utilized the MR images acquired by PAIR protocol to verify the result of the image segmentation.

UR - http://www.scopus.com/inward/record.url?scp=0030312442&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.1996.652717

DO - 10.1109/IEMBS.1996.652717

M3 - Conference article

AN - SCOPUS:0030312442

SN - 0589-1019

VL - 3

SP - 1079

EP - 1080

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - Proceedings of the 1996 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 5)

Y2 - 31 October 1996 through 3 November 1996

ER -

Cascade algorithm combined Kohonen feature map with fuzzy C-means applied in MR brain image segmentation

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