A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI

Hsian Min Chen; Hsin Che Wang; Yung Chieh Chang; Jyh Wen Chai; Clayton Chi Chang Chen; Chein I. Chang; Che Lun Hung

doi:10.1109/ISPAN-FCST-ISCC.2017.54

A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI

Hsian Min Chen, Hsin Che Wang, Yung Chieh Chang, Jyh Wen Chai, Clayton Chi Chang Chen, Chein I. Chang, Che Lun Hung

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Accurate quantification of brain tissues is a very challenging problem in neuroimaging, such as quantification of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), and white matter lesions (WMLs). However, on many cases brain tissues and white matter lesions cannot be segmented and separated simultaneously by current techniques. Recently, a TRIO algorithm (TRIOA) is proposed to integrate three algorithms, Independent Component Analysis (ICA), Support Vector Machine (SVM) and Fisher's Linear Discriminant Analysis (FLDA) (ICA+SVM+IFLDA) which can effectively classify GM, WM and CSF by considering MR images as multispectral images in the native coordinate space. This paper further extends TRIOA in conjunction with Band Expansion Process (BEP), called Extended TRIOA (ETRIOA), to classify brain tissues as well as WMLs simultaneously. The accuracy assessment of the ETRIOA was evaluated by using the similarity index. The conducted experimental results demonstrate the clinical applicability of ETRIOA in simultaneous classification of GM, WM, CSF and WMLs.

Original language	English
Title of host publication	Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	375-379
Number of pages	5
ISBN (Electronic)	9781538608401
DOIs	https://doi.org/10.1109/ISPAN-FCST-ISCC.2017.54
State	Published - 27 11 2017
Externally published	Yes
Event	14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017 - Exeter, Devon, United Kingdom Duration: 21 06 2017 → 23 06 2017

Publication series

Name	Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Volume	2017-November

Conference

Conference	14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Country/Territory	United Kingdom
City	Exeter, Devon
Period	21/06/17 → 23/06/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Band expansion process (BEP)
Brain MRI
Multispectral MRI
TRIOA

Access to Document

10.1109/ISPAN-FCST-ISCC.2017.54

Cite this

Chen, H. M., Wang, H. C., Chang, Y. C., Chai, J. W., Chen, C. C. C., Chang, C. I., & Hung, C. L. (2017). A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI. In Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017 (pp. 375-379). (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017; Vol. 2017-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISPAN-FCST-ISCC.2017.54

Chen, Hsian Min ; Wang, Hsin Che ; Chang, Yung Chieh et al. / A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI. Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 375-379 (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017).

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title = "A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI",

abstract = "Accurate quantification of brain tissues is a very challenging problem in neuroimaging, such as quantification of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), and white matter lesions (WMLs). However, on many cases brain tissues and white matter lesions cannot be segmented and separated simultaneously by current techniques. Recently, a TRIO algorithm (TRIOA) is proposed to integrate three algorithms, Independent Component Analysis (ICA), Support Vector Machine (SVM) and Fisher's Linear Discriminant Analysis (FLDA) (ICA+SVM+IFLDA) which can effectively classify GM, WM and CSF by considering MR images as multispectral images in the native coordinate space. This paper further extends TRIOA in conjunction with Band Expansion Process (BEP), called Extended TRIOA (ETRIOA), to classify brain tissues as well as WMLs simultaneously. The accuracy assessment of the ETRIOA was evaluated by using the similarity index. The conducted experimental results demonstrate the clinical applicability of ETRIOA in simultaneous classification of GM, WM, CSF and WMLs.",

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note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017 ; Conference date: 21-06-2017 Through 23-06-2017",

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pages = "375--379",

booktitle = "Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017",

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Chen, HM, Wang, HC, Chang, YC, Chai, JW, Chen, CCC, Chang, CI & Hung, CL 2017, A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI. in Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017, vol. 2017-November, Institute of Electrical and Electronics Engineers Inc., pp. 375-379, 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017, Exeter, Devon, United Kingdom, 21/06/17. https://doi.org/10.1109/ISPAN-FCST-ISCC.2017.54

A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI. / Chen, Hsian Min; Wang, Hsin Che; Chang, Yung Chieh et al.
Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 375-379 (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017; Vol. 2017-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Chen HM, Wang HC, Chang YC, Chai JW, Chen CCC, Chang CI et al. A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI. In Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 375-379. (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017). doi: 10.1109/ISPAN-FCST-ISCC.2017.54

A supervised hybrid classifier for brain tissues and white matter lesions on multispectral MRI

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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