Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method
An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. This method is suitable for problems in which the image can be modeled by explicit known source functions with a few adjustable...
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| Online Access: | http://irep.iium.edu.my/5452/ http://irep.iium.edu.my/5452/1/Optimal_Model_Order_Selection_for_Transient_Error.pdf |
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iium-54522012-06-11T07:04:25Z http://irep.iium.edu.my/5452/ Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method Aibinu, Abiodun Musa Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin T Technology (General) An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. This method is suitable for problems in which the image can be modeled by explicit known source functions with a few adjustable parameters. Despite the success reported in the use of modeling technique as an alternative MRI reconstruction technique, two important problems constitutes challenges to the applicability of this method, these are estimation of Model order and model coefficient determination. In this paper, five of the suggested method of evaluating the model order have been evaluated, these are: The Final Prediction Error (FPE), Akaike Information Criterion (AIC), Residual Variance (RV), Minimum Description Length (MDL) and Hannan and Quinn (HNQ) criterion. These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). The result for each criterion is compared to result obtained by the use of a fixed order technique and three measures of similarity were evaluated. Result obtained shows that the use of MDL gives the highest measure of similarity to that use by a fixed order technique. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/5452/1/Optimal_Model_Order_Selection_for_Transient_Error.pdf Aibinu, Abiodun Musa and Najeeb, Athaur Rahman and Salami, Momoh Jimoh Emiyoka and Shafie, Amir Akramin (2008) Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method. In: International Conference on Medical system Engineering (ICMSE). |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
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IIUM Repository |
| collection |
Online Access |
| language |
English |
| topic |
T Technology (General) |
| spellingShingle |
T Technology (General) Aibinu, Abiodun Musa Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method |
| description |
An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique. |
| format |
Conference or Workshop Item |
| author |
Aibinu, Abiodun Musa Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin |
| author_facet |
Aibinu, Abiodun Musa Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin |
| author_sort |
Aibinu, Abiodun Musa |
| title |
Optimal model order selection for Transient Error
Autoregressive Moving Average (TERA) MRI
reconstruction method |
| title_short |
Optimal model order selection for Transient Error
Autoregressive Moving Average (TERA) MRI
reconstruction method |
| title_full |
Optimal model order selection for Transient Error
Autoregressive Moving Average (TERA) MRI
reconstruction method |
| title_fullStr |
Optimal model order selection for Transient Error
Autoregressive Moving Average (TERA) MRI
reconstruction method |
| title_full_unstemmed |
Optimal model order selection for Transient Error
Autoregressive Moving Average (TERA) MRI
reconstruction method |
| title_sort |
optimal model order selection for transient error
autoregressive moving average (tera) mri
reconstruction method |
| publishDate |
2008 |
| url |
http://irep.iium.edu.my/5452/ http://irep.iium.edu.my/5452/1/Optimal_Model_Order_Selection_for_Transient_Error.pdf |
| first_indexed |
2023-09-18T20:14:04Z |
| last_indexed |
2023-09-18T20:14:04Z |
| _version_ |
1777407669563293696 |