A Novel Biomedical Image Classification Using Kernel Support Vector Machine

• Author(s): K. Leela Prasad ; K. Ganga Eswar ; Lokesh. G. ; K. Sai Krishna
• Paper ID: 1702207
• Page: 173-177
• Published Date: 28-04-2020
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 3 Issue 10 April-2020

Abstract

An accurate and automated type classification of MRI scan based brain images is more extremely important during medical analysis and interpretation of brain. From over past decade various methods have already been implemented. In this Project, we can use a novel method for the classification of a given MRI brain scan image as normal or abnormal. The proposed method that was first perform wavelet transform to extract original features from MRI scanned images, In next step we can apply principle component analysis in order to reduce the dimensions of features. Those features are submitted to a kernel support vector machine (KSVM) for classification of Brain Images for normal and abnormal. The strategy of K-fold stratified cross validation was used to enhance generalization of KSVM.

Keywords

Tumor, Digital Signal Processing, Matlab, Gesture MRI Scan, Vector Machine, Kernel

Citations

IRE Journals:
K. Leela Prasad , K. Ganga Eswar , Lokesh. G. , K. Sai Krishna "A Novel Biomedical Image Classification Using Kernel Support Vector Machine" Iconic Research And Engineering Journals Volume 3 Issue 10 2020 Page 173-177

IEEE:
K. Leela Prasad , K. Ganga Eswar , Lokesh. G. , K. Sai Krishna "A Novel Biomedical Image Classification Using Kernel Support Vector Machine" Iconic Research And Engineering Journals, 3(10)