Comput Math Methods Med - Ultrasound image enhancement using structure-based filtering.

Tópicos

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{ featur(3375) classif(2383) classifi(1994) }
{ imag(2675) segment(2577) method(1081) }
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{ featur(1941) imag(1645) propos(1176) }
{ model(2656) set(1616) predict(1553) }
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{ method(1557) propos(1049) approach(1037) }
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{ activ(1138) subject(705) human(624) }
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{ can(981) present(881) function(850) }
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{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

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.

Resumo Limpo

ultrasound imag prone speckl nois speckl blur featur essenti diagnosi assess thus despeckl necess ultrasound imag process linear filter can suppress speckl smooth featur median filter base despeckl algorithm produc better result howev may produc artifact pattern result imag oversmooth nonuniform region paper present innov despeckl procedur ultrasound imag propos method diffus tensor intens comput pixel first eigensystem diffus tensor calcul employ detect classifi under structur base classif result feasibl filter select suppress speckl enhanc featur test result show propos despeckl method reduc speckl uniform area enhanc tissu boundari spot

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