Ultrasound Image Enhancement Using Structure-Based Filtering
Ultrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produ...
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Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2014/758439 |
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doaj-f17defa573d34ea8bbe25a234d9d04492020-11-24T21:33:15ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182014-01-01201410.1155/2014/758439758439Ultrasound Image Enhancement Using Structure-Based FilteringShyh-Kuang Ueng0Cho-Li Yen1Guan-Zhi Chen2Department of Computer Science, National Taiwan Ocean University, No. 2, Peining Road, Keelung City 202, TaiwanChang-Gung Memorial Hospital, No. 222, Mai-Chin Road, Keelung City 204, TaiwanDepartment of Computer Science, National Taiwan Ocean University, No. 2, Peining Road, Keelung City 202, TaiwanUltrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produce better results. However, they may produce artifact patterns in the resulted images and oversmooth nonuniform regions. This paper presents an innovative despeckle procedure for ultrasound images. In the proposed method, the diffusion tensor of intensity is computed at each pixel at first. Then the eigensystem of the diffusion tensor is calculated and employed to detect and classify the underlying structure. Based on the classification result, a feasible filter is selected to suppress speckles and enhance features. Test results show that the proposed despeckle method reduces speckles in uniform areas and enhances tissue boundaries and spots.http://dx.doi.org/10.1155/2014/758439 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shyh-Kuang Ueng Cho-Li Yen Guan-Zhi Chen |
spellingShingle |
Shyh-Kuang Ueng Cho-Li Yen Guan-Zhi Chen Ultrasound Image Enhancement Using Structure-Based Filtering Computational and Mathematical Methods in Medicine |
author_facet |
Shyh-Kuang Ueng Cho-Li Yen Guan-Zhi Chen |
author_sort |
Shyh-Kuang Ueng |
title |
Ultrasound Image Enhancement Using Structure-Based Filtering |
title_short |
Ultrasound Image Enhancement Using Structure-Based Filtering |
title_full |
Ultrasound Image Enhancement Using Structure-Based Filtering |
title_fullStr |
Ultrasound Image Enhancement Using Structure-Based Filtering |
title_full_unstemmed |
Ultrasound Image Enhancement Using Structure-Based Filtering |
title_sort |
ultrasound image enhancement using structure-based filtering |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2014-01-01 |
description |
Ultrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produce
better results. However, they may produce artifact patterns in the resulted images and oversmooth nonuniform regions. This paper presents an innovative despeckle procedure for ultrasound images. In the proposed method,
the diffusion tensor of intensity is computed at each pixel at first. Then the eigensystem of the diffusion tensor is calculated and employed to detect and classify the underlying structure. Based on the classification result, a feasible filter is selected to suppress speckles and enhance features. Test results show that the proposed despeckle method reduces speckles in uniform areas and enhances tissue boundaries and spots. |
url |
http://dx.doi.org/10.1155/2014/758439 |
work_keys_str_mv |
AT shyhkuangueng ultrasoundimageenhancementusingstructurebasedfiltering AT choliyen ultrasoundimageenhancementusingstructurebasedfiltering AT guanzhichen ultrasoundimageenhancementusingstructurebasedfiltering |
_version_ |
1725954153007546368 |