Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising
The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2014-01-01
|
Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2014/810680 |
id |
doaj-9e26a407a9e740a4b6b51baa9a619c14 |
---|---|
record_format |
Article |
spelling |
doaj-9e26a407a9e740a4b6b51baa9a619c142020-11-24T22:39:23ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182014-01-01201410.1155/2014/810680810680Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI DenoisingRodney Jaramillo0Marianela Lentini1Marco Paluszny2Escuela de Matemáticas, Facultad de Ciencias, Universidad Nacional de Colombia, Medellín, ColombiaEscuela de Matemáticas, Facultad de Ciencias, Universidad Nacional de Colombia, Medellín, ColombiaEscuela de Matemáticas, Facultad de Ciencias, Universidad Nacional de Colombia, Medellín, ColombiaThe Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek’s algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T2 MR images, and the filter is applied to each image before using the variant of the Prony method.http://dx.doi.org/10.1155/2014/810680 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rodney Jaramillo Marianela Lentini Marco Paluszny |
spellingShingle |
Rodney Jaramillo Marianela Lentini Marco Paluszny Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising Computational and Mathematical Methods in Medicine |
author_facet |
Rodney Jaramillo Marianela Lentini Marco Paluszny |
author_sort |
Rodney Jaramillo |
title |
Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising |
title_short |
Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising |
title_full |
Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising |
title_fullStr |
Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising |
title_full_unstemmed |
Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising |
title_sort |
improving the performance of the prony method using a wavelet domain filter for mri denoising |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2014-01-01 |
description |
The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek’s algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T2 MR images, and the filter is applied to each image before using the variant of the Prony method. |
url |
http://dx.doi.org/10.1155/2014/810680 |
work_keys_str_mv |
AT rodneyjaramillo improvingtheperformanceofthepronymethodusingawaveletdomainfilterformridenoising AT marianelalentini improvingtheperformanceofthepronymethodusingawaveletdomainfilterformridenoising AT marcopaluszny improvingtheperformanceofthepronymethodusingawaveletdomainfilterformridenoising |
_version_ |
1725709107115065344 |