Artificial neural network based fast edge detection algorithm for MRI medical images

Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes...

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Main Authors:	Gunawan, Teddy Surya, Yaacob, Iza Zayana, Kartiwi, Mira, Ismail, Nanang, Za'bah, Nor Farahidah, Mansor, Hasmah
Format:	Article
Language:	English English
Published:	Institute of Advanced Engineering and Science 2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/58372/ http://irep.iium.edu.my/58372/ http://irep.iium.edu.my/58372/ http://irep.iium.edu.my/58372/7/58372_Artificial%20Neural%20Network%20Based%20Fast%20Edge.pdf http://irep.iium.edu.my/58372/8/58372_Artificial%20Neural%20Network%20Based%20Fast%20Edge_SCOPUS.pdf

id	iium-58372
recordtype	eprints
spelling	iium-583722018-04-03T07:28:40Z http://irep.iium.edu.my/58372/ Artificial neural network based fast edge detection algorithm for MRI medical images Gunawan, Teddy Surya Yaacob, Iza Zayana Kartiwi, Mira Ismail, Nanang Za'bah, Nor Farahidah Mansor, Hasmah TK Electrical engineering. Electronics Nuclear engineering Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector. Institute of Advanced Engineering and Science 2017-07 Article PeerReviewed application/pdf en http://irep.iium.edu.my/58372/7/58372_Artificial%20Neural%20Network%20Based%20Fast%20Edge.pdf application/pdf en http://irep.iium.edu.my/58372/8/58372_Artificial%20Neural%20Network%20Based%20Fast%20Edge_SCOPUS.pdf Gunawan, Teddy Surya and Yaacob, Iza Zayana and Kartiwi, Mira and Ismail, Nanang and Za'bah, Nor Farahidah and Mansor, Hasmah (2017) Artificial neural network based fast edge detection algorithm for MRI medical images. Indonesian Journal of Electrical Engineering and Computer Science, 7 (1). pp. 123-130. ISSN 2502-4752 E-ISSN 2502-4760 http://www.iaesjournal.com/online/index.php/IJEECS/issue/view/396 10.11591/ijeecs.v7.i1.pp123-130
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Gunawan, Teddy Surya Yaacob, Iza Zayana Kartiwi, Mira Ismail, Nanang Za'bah, Nor Farahidah Mansor, Hasmah Artificial neural network based fast edge detection algorithm for MRI medical images
description	Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.
format	Article
author	Gunawan, Teddy Surya Yaacob, Iza Zayana Kartiwi, Mira Ismail, Nanang Za'bah, Nor Farahidah Mansor, Hasmah
author_facet	Gunawan, Teddy Surya Yaacob, Iza Zayana Kartiwi, Mira Ismail, Nanang Za'bah, Nor Farahidah Mansor, Hasmah
author_sort	Gunawan, Teddy Surya
title	Artificial neural network based fast edge detection algorithm for MRI medical images
title_short	Artificial neural network based fast edge detection algorithm for MRI medical images
title_full	Artificial neural network based fast edge detection algorithm for MRI medical images
title_fullStr	Artificial neural network based fast edge detection algorithm for MRI medical images
title_full_unstemmed	Artificial neural network based fast edge detection algorithm for MRI medical images
title_sort	artificial neural network based fast edge detection algorithm for mri medical images
publisher	Institute of Advanced Engineering and Science
publishDate	2017
url	http://irep.iium.edu.my/58372/ http://irep.iium.edu.my/58372/ http://irep.iium.edu.my/58372/ http://irep.iium.edu.my/58372/7/58372_Artificial%20Neural%20Network%20Based%20Fast%20Edge.pdf http://irep.iium.edu.my/58372/8/58372_Artificial%20Neural%20Network%20Based%20Fast%20Edge_SCOPUS.pdf
first_indexed	2023-09-18T21:22:32Z
last_indexed	2023-09-18T21:22:32Z
_version_	1777411977206824960

Artificial neural network based fast edge detection algorithm for MRI medical images

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