MRI brain tumor segmentation: A forthright image processing approach
Brain tumor is a collection of cells that grow in an abnormal and uncontrollable way. It may affect the regular function of the brain since it grows inside the skull region. As a brain tumor can be possibly led to cancer, early detection in computed tomography (CT) or magnetic resonance imaging (MRI...
Published in: | Bulletin of Electrical Engineering and Informatics |
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Institute of Advanced Engineering and Science
2020
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2-s2.0-85083114686 Khalid N.E.A.; Ismail M.F.; Manaf M.A.A.B.; Fadzil A.F.A.; Ibrahim S. MRI brain tumor segmentation: A forthright image processing approach 2020 Bulletin of Electrical Engineering and Informatics 9 3 10.11591/eei.v9i3.2063 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083114686&doi=10.11591%2feei.v9i3.2063&partnerID=40&md5=50a9ab85ebe23693209bca729bb13268 Brain tumor is a collection of cells that grow in an abnormal and uncontrollable way. It may affect the regular function of the brain since it grows inside the skull region. As a brain tumor can be possibly led to cancer, early detection in computed tomography (CT) or magnetic resonance imaging (MRI) scanned images are crucial. Thus, this paper proposed a forthright image processing approach towards detection and localization of brain tumor region The approach consists of a few stages such as pre-processing, edge detection and segmentation. The pre-processing stage converts the original image into a greyscale image, and noise removal if necessary. Next, the image is enhanced using image enhancement techniques. It is then followed by edge detection using Sobel and Canny algorithms. Finally, the segmentation is applied to highlight the tumor with morphological operations towards the affected region in the MRI images. The in-depth analysis is measured using a confusion matrix. From the results, it signifies that the proposed approach is capable to provide decent segmentation of brain tumor from various MRI brain images. © 2020, Institute of Advanced Engineering and Science. All rights reserved. Institute of Advanced Engineering and Science 20893191 English Article All Open Access; Gold Open Access |
author |
Khalid N.E.A.; Ismail M.F.; Manaf M.A.A.B.; Fadzil A.F.A.; Ibrahim S. |
spellingShingle |
Khalid N.E.A.; Ismail M.F.; Manaf M.A.A.B.; Fadzil A.F.A.; Ibrahim S. MRI brain tumor segmentation: A forthright image processing approach |
author_facet |
Khalid N.E.A.; Ismail M.F.; Manaf M.A.A.B.; Fadzil A.F.A.; Ibrahim S. |
author_sort |
Khalid N.E.A.; Ismail M.F.; Manaf M.A.A.B.; Fadzil A.F.A.; Ibrahim S. |
title |
MRI brain tumor segmentation: A forthright image processing approach |
title_short |
MRI brain tumor segmentation: A forthright image processing approach |
title_full |
MRI brain tumor segmentation: A forthright image processing approach |
title_fullStr |
MRI brain tumor segmentation: A forthright image processing approach |
title_full_unstemmed |
MRI brain tumor segmentation: A forthright image processing approach |
title_sort |
MRI brain tumor segmentation: A forthright image processing approach |
publishDate |
2020 |
container_title |
Bulletin of Electrical Engineering and Informatics |
container_volume |
9 |
container_issue |
3 |
doi_str_mv |
10.11591/eei.v9i3.2063 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083114686&doi=10.11591%2feei.v9i3.2063&partnerID=40&md5=50a9ab85ebe23693209bca729bb13268 |
description |
Brain tumor is a collection of cells that grow in an abnormal and uncontrollable way. It may affect the regular function of the brain since it grows inside the skull region. As a brain tumor can be possibly led to cancer, early detection in computed tomography (CT) or magnetic resonance imaging (MRI) scanned images are crucial. Thus, this paper proposed a forthright image processing approach towards detection and localization of brain tumor region The approach consists of a few stages such as pre-processing, edge detection and segmentation. The pre-processing stage converts the original image into a greyscale image, and noise removal if necessary. Next, the image is enhanced using image enhancement techniques. It is then followed by edge detection using Sobel and Canny algorithms. Finally, the segmentation is applied to highlight the tumor with morphological operations towards the affected region in the MRI images. The in-depth analysis is measured using a confusion matrix. From the results, it signifies that the proposed approach is capable to provide decent segmentation of brain tumor from various MRI brain images. © 2020, Institute of Advanced Engineering and Science. All rights reserved. |
publisher |
Institute of Advanced Engineering and Science |
issn |
20893191 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809678482208194560 |