CLASSIFICATION OF KIDNEY ULTRASOUND IMAGES USING SVM CLASSIFIER

CLASSIFICATION OF KIDNEY ULTRASOUND IMAGES USING SVM CLASSIFIER
Author(s):
S. Mehar Koushik, P.V.K Durga Prasad, R.Tejaswini, S. Seshank Varma, S.Mohit, K. Durga Prasad
Keywords:
Feature Extraction, GLCM, Image Acquisition, PCM, SVM.
Abstract
Medical Imaging applications in hospitals and laboratories have shown benefits in visualizing patient’s body for diagnosis and treatment of disease. Ultrasound is considered as safest medical imaging technique and is therefore used extensively in medical and healthcare using computer aided system. In this project, four stage detection of kidney disease is implemented. Feature extraction process is proposed using GLCM features. Finally obtained features are reduced to optimal subset using principal component analysis (PCA). The results show that GLCM in combination with PCA for feature reduction gives high classification accuracy when classifying images using Support Vector Machine (SVM). This project Evaluated by mat lab tool.
Article Details
Unique Paper ID: 155659 Publication Volume & Issue: Volume 9, Issue 1 Page(s): 1424 - 1427
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