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
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Online Access:http://eprints.usm.my/43992/1/MOHAMMAD%20MOHAMMAD%20SAID%20SHEHAB.pdf
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Institution: Universiti Sains Malaysia
Language: English
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spelling my.usm.eprints.43992 http://eprints.usm.my/43992/ Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function 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 NonPeerReviewed application/pdf en http://eprints.usm.my/43992/1/MOHAMMAD%20MOHAMMAD%20SAID%20SHEHAB.pdf Shehab, Mohammad Mohammad Said (2018) Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function. PhD thesis, Universiti Sains Malaysia.
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 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
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
publishDate 2018
url http://eprints.usm.my/43992/1/MOHAMMAD%20MOHAMMAD%20SAID%20SHEHAB.pdf
http://eprints.usm.my/43992/
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