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Author: search.filters.author.Wongsita, PichetSubject: search.filters.subject.Feature extraction

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    Feature extraction in medical ultrasonic image
    (2007-01-01)
    Udomhunsakul, Somkait
    ;
    Wongsita, Pichet
    This 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.
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    Feature extraction in medical MRI images
    (2004-12-01)
    Udomhunsakul, Somkait
    ;
    Wongsita, Pichet
    A feature extraction approach in medical magnetic resonance imaging (MRI) is proposed. In this approach, first the combination of spatial filters using the 5×5 wiener filter followed by a 3×3 Gaussian filter is used to remove the noisy pixels while preserving the important information. Next, the edge detection algorithm based on multiple-scales edge detection of Gabor filters is applied. Moreover, Wavelet transform based image fusion is used to combine the detail coefficients. Finally, the nonmaxima suppression technique is adopted to get the final result. The experiments show that the proposed algorithm can be detected well-localized, and thin edges. Therefore, the algorithm leads to a useful method for feature extraction in MRI images and can be used for diagnostic purposes.