Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function

The Diffusion-Weighted Magnetic Resonance Imaging(DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. The raw data acquired from the MRI scanner may not be directly usable by the specialists. Therefore, new methods are required to make more re...

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Main Author:	Shehab, Mohammad Mohammad Said
Format:	Thesis
Language:	English
Published:	2018
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/43992/1/MOHAMMAD%20MOHAMMAD%20SAID%20SHEHAB.pdf
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id	my-usm-ep.43992
record_format	uketd_dc
spelling	my-usm-ep.439922019-04-12T05:24:50Z Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function 2018-06 Shehab, Mohammad Mohammad Said QA75.5-76.95 Electronic computers. Computer science The Diffusion-Weighted Magnetic Resonance Imaging(DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. The raw data acquired from the MRI scanner may not be directly usable by the specialists. Therefore, new methods are required to make more reasonable representations of the data to extract the required information from them. The initial representation of the MRI data is the huge groups of fibers. These fibers contain fiber crossing bundles, which link the functional brain areas all together as a complex net-work of neural fiber tracts. Q-ball imaging (QBI) is a Diffusion MRI reconstruction technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MRI (i.e., fiber crossing) based on the standard computation of the Orientation Distribution Function (ODF), which is a 3- Dimension spherical function founded to detect the dominant fiber orientations in the underlying volume of a pixel (voxel). 2018-06 Thesis http://eprints.usm.my/43992/ http://eprints.usm.my/43992/1/MOHAMMAD%20MOHAMMAD%20SAID%20SHEHAB.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Shehab, Mohammad Mohammad Said Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
description	The Diffusion-Weighted Magnetic Resonance Imaging(DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. The raw data acquired from the MRI scanner may not be directly usable by the specialists. Therefore, new methods are required to make more reasonable representations of the data to extract the required information from them. The initial representation of the MRI data is the huge groups of fibers. These fibers contain fiber crossing bundles, which link the functional brain areas all together as a complex net-work of neural fiber tracts. Q-ball imaging (QBI) is a Diffusion MRI reconstruction technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MRI (i.e., fiber crossing) based on the standard computation of the Orientation Distribution Function (ODF), which is a 3- Dimension spherical function founded to detect the dominant fiber orientations in the underlying volume of a pixel (voxel).
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Shehab, Mohammad Mohammad Said
author_facet	Shehab, Mohammad Mohammad Said
author_sort	Shehab, Mohammad Mohammad Said
title	Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
title_short	Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
title_full	Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
title_fullStr	Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
title_full_unstemmed	Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
title_sort	enhanced cuckoo search algorithm with metaheuristic components for extracting the maxima of the orientation distribution function
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer
publishDate	2018
url	http://eprints.usm.my/43992/1/MOHAMMAD%20MOHAMMAD%20SAID%20SHEHAB.pdf
_version_	1747821314773614592

Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function

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