Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm

The use of parametric modelling approach for Magnetic Resonance Imaging (MRI) reconstruction has been shown to produce images with higher resolution compared to the use of Fast Fourier Transform (FFT) technique. Despite this success, two problems lessen the use of this technique, these are: non avai...

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Main Authors:	Salami, Momoh Jimoh Emiyoka, Najeeb, Athaur Rahman
Format:	Monograph
Language:	English
Published:	[s.n] 2012
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://irep.iium.edu.my/31212/ http://irep.iium.edu.my/31212/1/FULL_VERSION_OF_RESEARCH_REPORT.docx

id	iium-31212
recordtype	eprints
spelling	iium-312122013-09-17T07:20:27Z http://irep.iium.edu.my/31212/ Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm Salami, Momoh Jimoh Emiyoka Najeeb, Athaur Rahman TA Engineering (General). Civil engineering (General) The use of parametric modelling approach for Magnetic Resonance Imaging (MRI) reconstruction has been shown to produce images with higher resolution compared to the use of Fast Fourier Transform (FFT) technique. Despite this success, two problems lessen the use of this technique, these are: non availability of optimal method of estimating model order and the model coefficients determination. In this research work, a new method of Autoregressive Moving Average (ARMA) coefficients using three layer complex valued neural network ARMA techniques (CVNN-CARMA) with split complex-value weight and adaptive linear activation functions is hereby proposed. The proposed model coefficients determination in conjunction with various methods of optimal model order determination were then applied on MRI data using both Transient Error Reconstruction Algorithm (TERA) and modified Transient Error Reconstruction Algorithm to obtain images with improved resolution. Future work include extending this modelling method to two dimensional domain, evaluating the performance of the proposed CVNN-CARMA and using a trained artificial neural network to automatically obtain the model order of a complex valued data. Keywords: Autoregressive Model Algorithm (ARMA), Magnetic Resonance Imaging (MRI), Reconstruction [s.n] 2012-12-29 Monograph NonPeerReviewed application/pdf en http://irep.iium.edu.my/31212/1/FULL_VERSION_OF_RESEARCH_REPORT.docx Salami, Momoh Jimoh Emiyoka and Najeeb, Athaur Rahman (2012) Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm. Research Report. [s.n]. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Salami, Momoh Jimoh Emiyoka Najeeb, Athaur Rahman Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
description	The use of parametric modelling approach for Magnetic Resonance Imaging (MRI) reconstruction has been shown to produce images with higher resolution compared to the use of Fast Fourier Transform (FFT) technique. Despite this success, two problems lessen the use of this technique, these are: non availability of optimal method of estimating model order and the model coefficients determination. In this research work, a new method of Autoregressive Moving Average (ARMA) coefficients using three layer complex valued neural network ARMA techniques (CVNN-CARMA) with split complex-value weight and adaptive linear activation functions is hereby proposed. The proposed model coefficients determination in conjunction with various methods of optimal model order determination were then applied on MRI data using both Transient Error Reconstruction Algorithm (TERA) and modified Transient Error Reconstruction Algorithm to obtain images with improved resolution. Future work include extending this modelling method to two dimensional domain, evaluating the performance of the proposed CVNN-CARMA and using a trained artificial neural network to automatically obtain the model order of a complex valued data. Keywords: Autoregressive Model Algorithm (ARMA), Magnetic Resonance Imaging (MRI), Reconstruction
format	Monograph
author	Salami, Momoh Jimoh Emiyoka Najeeb, Athaur Rahman
author_facet	Salami, Momoh Jimoh Emiyoka Najeeb, Athaur Rahman
author_sort	Salami, Momoh Jimoh Emiyoka
title	Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
title_short	Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
title_full	Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
title_fullStr	Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
title_full_unstemmed	Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
title_sort	performance analysis of arma based magnetic resonance imaging (mri) reconstruction algorithm
publisher	[s.n]
publishDate	2012
url	http://irep.iium.edu.my/31212/ http://irep.iium.edu.my/31212/1/FULL_VERSION_OF_RESEARCH_REPORT.docx
first_indexed	2018-09-07T05:20:41Z
last_indexed	2018-09-07T05:20:41Z
_version_	1610924835761815552

Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm

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