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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Main Authors: Shyh-Kuang Ueng, Cho-Li Yen, Guan-Zhi Chen
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2014/758439
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spelling 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
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