Modified magnetic resonance image based parcellation method for cerebral cortex using successive fuzzy clustering and boundary detection

Uicheul Yoon; Jong Min Lee; Jae Jin Kim; Sang Min Lee; In Young Kim; Jun Soo Kwon; Sun I. Kim

doi:10.1114/1.1557973

Modified magnetic resonance image based parcellation method for cerebral cortex using successive fuzzy clustering and boundary detection

Uicheul Yoon, Jong Min Lee, Jae Jin Kim, Sang Min Lee, In Young Kim, Jun Soo Kwon, Sun I. Kim

Department of Psychiatry

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

A modified parcellation method of the cerebral cortex based on T1-weighted MRI is proposed. Although the method is considerably dependent on the performance of classification algorithm, it provides reliable and reproducible ROI, using successive fuzzy clustering to improve the efficiency of classification and boundary-detection algorithm to establish easily ROI on a tissue-classified image. In general, the method is fairly independent of the anatomical variability.

Original language	English
Pages (from-to)	441-447
Number of pages	7
Journal	Annals of Biomedical Engineering
Volume	31
Issue number	4
DOIs	https://doi.org/10.1114/1.1557973
Publication status	Published - 2003

Bibliographical note

Funding Information:
This work is the result of research activities of Advanced Biometric Research Center (ABRC) (R11-2001-09401002-0) supported by the Korea Science and Engineering Foundation (KOSEF).

All Science Journal Classification (ASJC) codes

Biomedical Engineering

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10.1114/1.1557973

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abstract = "A modified parcellation method of the cerebral cortex based on T1-weighted MRI is proposed. Although the method is considerably dependent on the performance of classification algorithm, it provides reliable and reproducible ROI, using successive fuzzy clustering to improve the efficiency of classification and boundary-detection algorithm to establish easily ROI on a tissue-classified image. In general, the method is fairly independent of the anatomical variability.",

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note = "Funding Information: This work is the result of research activities of Advanced Biometric Research Center (ABRC) (R11-2001-09401002-0) supported by the Korea Science and Engineering Foundation (KOSEF).",

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AU - Yoon, Uicheul

AU - Lee, Jong Min

AU - Kim, Jae Jin

AU - Lee, Sang Min

AU - Kim, In Young

AU - Kwon, Jun Soo

AU - Kim, Sun I.

N1 - Funding Information: This work is the result of research activities of Advanced Biometric Research Center (ABRC) (R11-2001-09401002-0) supported by the Korea Science and Engineering Foundation (KOSEF).

PY - 2003

Y1 - 2003

N2 - A modified parcellation method of the cerebral cortex based on T1-weighted MRI is proposed. Although the method is considerably dependent on the performance of classification algorithm, it provides reliable and reproducible ROI, using successive fuzzy clustering to improve the efficiency of classification and boundary-detection algorithm to establish easily ROI on a tissue-classified image. In general, the method is fairly independent of the anatomical variability.

AB - A modified parcellation method of the cerebral cortex based on T1-weighted MRI is proposed. Although the method is considerably dependent on the performance of classification algorithm, it provides reliable and reproducible ROI, using successive fuzzy clustering to improve the efficiency of classification and boundary-detection algorithm to establish easily ROI on a tissue-classified image. In general, the method is fairly independent of the anatomical variability.

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Modified magnetic resonance image based parcellation method for cerebral cortex using successive fuzzy clustering and boundary detection

Abstract

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All Science Journal Classification (ASJC) codes

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