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Authors
Affiliations
1 Mahavidyalayam Arts and Science College
for Women, Ulundurpet, Tamil Nadu, IN
2 Department of Computer Science and Applications, Tiruvalluvar University College for Arts and Science, Thiruvennainallur, IN
Source
Digital Image Processing, Vol 7, No 9 (2015), Pagination: 268-272
Abstract
Carotid ultrasound plaque classification using a combination of .region of interest, discrete wavelet transform and neural networks are used to classify the symptomatic or asymptomatic ultrasound plaque images. The system involves three steps: 1) the preprocessing step using the ROI technique. 2) The method Feature extraction is done by averaging values and discrete wavelet transform.3) Classification using a Neural Network. In this work Multilayer feed-forward neural network is adapted for training and testing the images. The accuracy of 70% is obtained in proposed work using neural network classifier.
Keywords
Atherosclerosis, Carotid Ultrasound, Classification, Discrete Wavelet Transform (DWT), Region of Interest (ROI) Technique, Neural Network.
