Texture Classification of Diffused Liver Diseases Using Wavelet Transforms

Mostafa, A. and Ahmadian, A. and Abolhasani, M. J. and Gitie, M. (2005) Texture Classification of Diffused Liver Diseases Using Wavelet Transforms. Iranian Journal of Medical Physics, 2 (2). pp. 67-76.

IJMP_Volume 2_Issue 2_Pages 67-76.pdf

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Introduction: A major problem facing the patients with chronic liver diseases is the diagnostic procedure. The conventional diagnostic method depends mainly on needle biopsy which is an invasive method. There are  some  approaches  to  develop  a  reliable  noninvasive  method  of  evaluating  histological  changes  in sonograms. The main characteristic used to distinguish between the normal, hepatitis and cirrhosis liver is the texture of liver surface. The problem of defining a set of meaningful features that explores the characteristics of the texture, leads to several methods of determining tissue texture. Some of these methods, which have been developed so far, are based on wavelet transform. The selection of wavelet transform type affects the accuracy of determining the texture. In this study, an optimal wavelet transform called Gabor wavelet was introduced and three different methods of determining tissue texture were evaluated. These include statistical, dyadic wavelet transform and Gabor wavelet transform methods.   Materials and Methods: The proposed algorithm was applied to differentiate ultrasonic liver images into two disease states (hepatitis and cirrhosis) and normal liver. In this experiment, 50 liver sample images for each three states which already been proven by needle biopsy were used. These images are taken from a Toshiba Sonolayer SSA250A device using a 3.75 MHz transducer. For each image, a region of interest (ROI) with 75Ã�35 pixels is selected. The ROI is chosen to include only liver tissue without major blood vessel or hepatic duct. The  classification  method  used  for  this  work  is Â

Item Type: Article
Subjects: WN Radiology . Diagnostic Imaging
Divisions: Journals > Iranian J Medical Physics
Depositing User: ijmp ijmp
Date Deposited: 21 Jan 2018 15:38
Last Modified: 21 Jan 2018 15:38
URI: http://eprints.mums.ac.ir/id/eprint/9005

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