ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

1. ABSTRACT
DIGITAL ULTRASOUND DESPECKLING FOR AUTOMATIC
SEGMENTATION
Ali S. Saad 1 ,
Noise is the main factor which hampers the visual quality of ultrasound images. The
noise in such images is called "speckle" can be modeled as a random multiplicative
process. Computerized speckle reduction techniques are applied to digital ultrasound
images in order to reduce the noise level and improve the automated segmentation
process. Several results prove that wavelet filtering perform the best for speckle
reduction in digital ultrasound images. Other results on x-ray images compared wavelet
filtering with multi-scale contrast enhancement prove that the last one performs better.
The purpose of this study is to compare the two filtering approaches for speckle
reduction on digital ultrasound images as preprocessing step before applying
unsupervised segmentation.
The first method uses the wavelet soft threshold (WST) approach for speckle reduction.
The second method is based on multi-scale contrast enhancement. This approach is
constructed from the combination of a smoothing and derivative of the image. Contrast
enhancement is applied on local scale by using varying size of median filter.
The two methods were applied to synthetic and real ultrasound images. A comparison
between WST and multi-scale contrast enhancement method was also carried out.
Application of these methods to the ultrasonic images proved that there was a
significant improvement of the visual quality of the ultrasound images and more
accurate precision of the automated and unsupervised segmentation of real ultrasound
images.
The comparison confirmed that WST filtering gives better results than the other one as
preprocessing process for unsupervised segmentation of ultrasound images.
1 Associate Professor, Dept. of Biomedical Technology, College of applied medical sciences, King Saud
University P.O. Box 10219, Riyadh 11433, Kingdom of Saudi Arabia, Emails: alisaad@ksu.edu.sa
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