Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor

Brain segmentation is a process of segmenting brain from the non-brain components. It is also equivalent to skull stripping or brain extraction where the objective is to extract only brain tissue components. It is important to segment brain from the non-brain components since it is a preliminary ste...

Full description

Saved in:

Bibliographic Details
Main Author:	Abu Mangshor, Nur Nabilah
Format:	Thesis
Language:	English
Published:	2010
Subjects:	Indexes (General)
Online Access:	https://ir.uitm.edu.my/id/eprint/64279/1/64279.PDF
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.64279
record_format	uketd_dc
spelling	my-uitm-ir.642792023-07-20T01:58:54Z Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor 2010 Abu Mangshor, Nur Nabilah Indexes (General) Brain segmentation is a process of segmenting brain from the non-brain components. It is also equivalent to skull stripping or brain extraction where the objective is to extract only brain tissue components. It is important to segment brain from the non-brain components since it is a preliminary step in any further brain analysis and it will contribute great importance for extension in clinical study. This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. Numbers of clusters, K are determined manually and the difference between pixel grayscale values is used for measuring similarities. Mean calculation is used for calculating new centroid values during each iteration. The clustering process is continued until the centroid values no longer move. Experiments are conducted and the prototype system is tested with 30 FLAIR brain MRI. Results from the experiments showed that the prototype system managed to obtained 75.93% accuracy rate from the segmentation. This research can be improved in future by hybrid K-Means Clustering algorithm with any existing segmentation techniques. 2010 Thesis https://ir.uitm.edu.my/id/eprint/64279/ https://ir.uitm.edu.my/id/eprint/64279/1/64279.PDF text en public degree Universiti Teknologi Mara (UiTM) Faculty of Computer and Mathematical Sciences Jamil, Nursuriati (Assoc. Prof. Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Jamil, Nursuriati (Assoc. Prof. Dr.)
topic	Indexes (General)
spellingShingle	Indexes (General) Abu Mangshor, Nur Nabilah Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
description	Brain segmentation is a process of segmenting brain from the non-brain components. It is also equivalent to skull stripping or brain extraction where the objective is to extract only brain tissue components. It is important to segment brain from the non-brain components since it is a preliminary step in any further brain analysis and it will contribute great importance for extension in clinical study. This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. Numbers of clusters, K are determined manually and the difference between pixel grayscale values is used for measuring similarities. Mean calculation is used for calculating new centroid values during each iteration. The clustering process is continued until the centroid values no longer move. Experiments are conducted and the prototype system is tested with 30 FLAIR brain MRI. Results from the experiments showed that the prototype system managed to obtained 75.93% accuracy rate from the segmentation. This research can be improved in future by hybrid K-Means Clustering algorithm with any existing segmentation techniques.
format	Thesis
qualification_level	Bachelor degree
author	Abu Mangshor, Nur Nabilah
author_facet	Abu Mangshor, Nur Nabilah
author_sort	Abu Mangshor, Nur Nabilah
title	Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
title_short	Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
title_full	Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
title_fullStr	Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
title_full_unstemmed	Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
title_sort	segmentation of flair magnetic resonance brain images using k-means clustering algorithm / nur nabilah abu mangshor
granting_institution	Universiti Teknologi Mara (UiTM)
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2010
url	https://ir.uitm.edu.my/id/eprint/64279/1/64279.PDF
_version_	1783735432832352256

Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor

Similar Items