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Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques

Tumor classification using image processing techniques is becoming a powerful tool nowadays. Based on the importance of this technique, the motivation of this review paper is to present the chronology of brain tumor classification using the digital images and govern the mathematical modeling and sim...

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Main Authors:	Alias, N., Alwesabi, Y., Al-Rahmi, W. M.
Format:	Article
Language:	English
Published:	Asian Research Publishing Network 2017
Subjects:	Q Science (General)
Online Access:	http://eprints.utm.my/id/eprint/81182/1/NormaAlias2017_ChronologyofBrainTumorClassificationofIntelligent.pdf http://eprints.utm.my/id/eprint/81182/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:126244
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spelling	my.utm.811822019-07-24T03:35:16Z http://eprints.utm.my/id/eprint/81182/ Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques Alias, N. Alwesabi, Y. Al-Rahmi, W. M. Q Science (General) Tumor classification using image processing techniques is becoming a powerful tool nowadays. Based on the importance of this technique, the motivation of this review paper is to present the chronology of brain tumor classification using the digital images and govern the mathematical modeling and simulation of intelligent systems. The intelligent system involves artificial neural network (ANN), fuzzy logic (FL), support vector machine (SVM), and parallel support vector machine (PSVM). The chronology of brain tumor classification presents the latest part of the literature reviews related to the principal, type and interpretation of segmentation and classification of brain tumors via the large digital dataset from magnetic resonance imaging (MRI) images. This paper has been classified the modeling and simulation in classical and automatic models. Around 115 literature reviews in high ranking journal and high citation index are referred. This paper contains 6 contents, including mathematical modeling, numerical simulation, image processing, numerical results and performance, lastly is the conclusion to standardize the frame concept for the future of chronological framework involving the mathematical modeling and simulation. Research outcome to differentiate the tumor classification based on MRI images, modeling and simulation. Future work outlier in segmentation and classification are given in conclusion. Asian Research Publishing Network 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/81182/1/NormaAlias2017_ChronologyofBrainTumorClassificationofIntelligent.pdf Alias, N. and Alwesabi, Y. and Al-Rahmi, W. M. (2017) Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques. Journal of Theoretical and Applied Information Technology, 95 (19). pp. 4949-4963. ISSN 1992-8645 http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:126244
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Alias, N. Alwesabi, Y. Al-Rahmi, W. M. Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
description	Tumor classification using image processing techniques is becoming a powerful tool nowadays. Based on the importance of this technique, the motivation of this review paper is to present the chronology of brain tumor classification using the digital images and govern the mathematical modeling and simulation of intelligent systems. The intelligent system involves artificial neural network (ANN), fuzzy logic (FL), support vector machine (SVM), and parallel support vector machine (PSVM). The chronology of brain tumor classification presents the latest part of the literature reviews related to the principal, type and interpretation of segmentation and classification of brain tumors via the large digital dataset from magnetic resonance imaging (MRI) images. This paper has been classified the modeling and simulation in classical and automatic models. Around 115 literature reviews in high ranking journal and high citation index are referred. This paper contains 6 contents, including mathematical modeling, numerical simulation, image processing, numerical results and performance, lastly is the conclusion to standardize the frame concept for the future of chronological framework involving the mathematical modeling and simulation. Research outcome to differentiate the tumor classification based on MRI images, modeling and simulation. Future work outlier in segmentation and classification are given in conclusion.
format	Article
author	Alias, N. Alwesabi, Y. Al-Rahmi, W. M.
author_facet	Alias, N. Alwesabi, Y. Al-Rahmi, W. M.
author_sort	Alias, N.
title	Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
title_short	Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
title_full	Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
title_fullStr	Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
title_full_unstemmed	Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
title_sort	chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques
publisher	Asian Research Publishing Network
publishDate	2017
url	http://eprints.utm.my/id/eprint/81182/1/NormaAlias2017_ChronologyofBrainTumorClassificationofIntelligent.pdf http://eprints.utm.my/id/eprint/81182/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:126244
_version_	1643658634649927680
score	13.211869

Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques

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