CLASSIFICATION OF KIDNEY ULTRASOUND IMAGES USING SVM CLASSIFIER

S. Mehar Koushik; P.V.K Durga Prasad; R.Tejaswini; S. Seshank Varma; S.Mohit; K. Durga Prasad

CLASSIFICATION OF KIDNEY ULTRASOUND IMAGES USING SVM CLASSIFIER

Authors: S. Mehar Koushik, P.V.K Durga Prasad, R.Tejaswini, S. Seshank Varma, S.Mohit, K. Durga Prasad

Unique Paper ID: 155659
Volume: 9
Issue: 1
PageNo: 1424-1427

Keywords: Feature Extraction GLCM Image Acquisition PCM SVM.

Abstract:
Medical Imaging applications in hospitals and laboratories have shown benefits in visualizing patientâ€™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.

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ISSN: 2349-6002
Volume: 9
Issue: 1
PageNo: 1424-1427

CLASSIFICATION OF KIDNEY ULTRASOUND IMAGES USING SVM CLASSIFIER

Available:https://ijirt.org/Article?manuscript=155659

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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