Investigation Of Edge Detection Techniques Based On Brain Tumor Images

Medical image processing has become an important technique that can visualize the interior of a human body for better diagnosis and extraction of an anatomical structure. Image processing has an advantage which reproduced original data repetitively without any changes that helps radiologist for anal...

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主要作者: Rosnan, Murni Nur Athirah
格式: Monograph
语言:English
出版: Universiti Sains Malaysia 2018
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在线阅读:http://eprints.usm.my/53566/1/Investigation%20Of%20Edge%20Detection%20Techniques%20Based%20On%20Brain%20Tumor%20Images_Murni%20Nur%20Athirah%20Rosnan_E3_2018.pdf
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spelling my.usm.eprints.53566 http://eprints.usm.my/53566/ Investigation Of Edge Detection Techniques Based On Brain Tumor Images Rosnan, Murni Nur Athirah T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Medical image processing has become an important technique that can visualize the interior of a human body for better diagnosis and extraction of an anatomical structure. Image processing has an advantage which reproduced original data repetitively without any changes that helps radiologist for analysis. Magnetic Resonance Imaging(MRI) is one of the medical imaging modalities that depend on computer technology to create detailed images of the brain. The output image by MRI need to undergo several imaging techniques to extract the important information accurately. In this work, all input MRI brain images are in DICOM format. The images undergo three fundamental steps of edge detection techniques. The edge detection operators used to detect the brain tumor are Robert zero-crossing, Sobel operator, Prewitt operator, Canny operator and modified Canny algorithm. The visual results from each operators are analyzed using quantitative and qualitative measurement. The quantitative parameters used to evaluate the operators performances are PSNR, MSE and SSIM. Based on the quantitative analysis, the new Canny algorithm successfully produced high quality image with less error. However, from visual perspective, Sobel operator produced better edge maps of the brain tumor compared to the Modified Canny algorithm. Universiti Sains Malaysia 2018-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53566/1/Investigation%20Of%20Edge%20Detection%20Techniques%20Based%20On%20Brain%20Tumor%20Images_Murni%20Nur%20Athirah%20Rosnan_E3_2018.pdf Rosnan, Murni Nur Athirah (2018) Investigation Of Edge Detection Techniques Based On Brain Tumor Images. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik dan Elektronik. (Submitted)
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
spellingShingle T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
Rosnan, Murni Nur Athirah
Investigation Of Edge Detection Techniques Based On Brain Tumor Images
description Medical image processing has become an important technique that can visualize the interior of a human body for better diagnosis and extraction of an anatomical structure. Image processing has an advantage which reproduced original data repetitively without any changes that helps radiologist for analysis. Magnetic Resonance Imaging(MRI) is one of the medical imaging modalities that depend on computer technology to create detailed images of the brain. The output image by MRI need to undergo several imaging techniques to extract the important information accurately. In this work, all input MRI brain images are in DICOM format. The images undergo three fundamental steps of edge detection techniques. The edge detection operators used to detect the brain tumor are Robert zero-crossing, Sobel operator, Prewitt operator, Canny operator and modified Canny algorithm. The visual results from each operators are analyzed using quantitative and qualitative measurement. The quantitative parameters used to evaluate the operators performances are PSNR, MSE and SSIM. Based on the quantitative analysis, the new Canny algorithm successfully produced high quality image with less error. However, from visual perspective, Sobel operator produced better edge maps of the brain tumor compared to the Modified Canny algorithm.
format Monograph
author Rosnan, Murni Nur Athirah
author_facet Rosnan, Murni Nur Athirah
author_sort Rosnan, Murni Nur Athirah
title Investigation Of Edge Detection Techniques Based On Brain Tumor Images
title_short Investigation Of Edge Detection Techniques Based On Brain Tumor Images
title_full Investigation Of Edge Detection Techniques Based On Brain Tumor Images
title_fullStr Investigation Of Edge Detection Techniques Based On Brain Tumor Images
title_full_unstemmed Investigation Of Edge Detection Techniques Based On Brain Tumor Images
title_sort investigation of edge detection techniques based on brain tumor images
publisher Universiti Sains Malaysia
publishDate 2018
url http://eprints.usm.my/53566/1/Investigation%20Of%20Edge%20Detection%20Techniques%20Based%20On%20Brain%20Tumor%20Images_Murni%20Nur%20Athirah%20Rosnan_E3_2018.pdf
http://eprints.usm.my/53566/
_version_ 1739828996070178816
score 13.153385