Feature extraction in medical ultrasonic image

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dc.contributor.authorUdomhunsakul, Somkait
dc.contributor.authorWongsita, Pichet
dc.date.accessioned2026-08-06T09:55:00Z
dc.date.available2026-08-06T09:55:00Z
dc.date.issued2007-01-01
dc.description.abstractThis paper presents a method for speckle noise reduction as well as feature extraction in medical ultrasonic images to effectively reduce the speckle noise and extract the object in ultrasonic images. In noise reduction process, the logarithm transform of the ultrasonic image is analyzed into wavelet domain by using 2D stationary wavelet transform (SWT). Next, the Weiner filter is used to apply over areas in each subband (HH, HL, LH and LL). Finally, the inverse wavelet transform is computed and applying the exponential. In feature extraction process, first the denoised image is enhanced by histogram equalization technique. Haar filter is used to extract the object. Moreover, nonmaxima suppression technique is adopted to get the edge localization. Finally, the adaptive hysteresis thresholding is applied to get the final result. The experiments show that the proposed algorithm can be detected well-localized and thin edges.
dc.identifier.citationIfmbe Proceedings, 15, 267-270, 2007
dc.identifier.doi10.1007/978-3-540-68017-8_69
dc.identifier.issn16800737
dc.identifier.other2-s2.0-84928881037
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/1547
dc.sourceIfmbe Proceedings
dc.subjectFeature extraction
dc.subjectNonmaxima suppression
dc.subjectSpeckle noise reduction
dc.subjectStationary Wavelet Transform
dc.titleFeature extraction in medical ultrasonic image
dc.typeConference Paper

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