Classification of medical X-ray images using supervised and unsupervised learning approaches

Most of the traditional approaches for medical image storage are least capable and scanning relevant matching images quite difficult. The existing content-based retrieval (C-BIR) less focused with images. available research works fuzzy logic very not efficient retrieval. Thus, there is a need work that can address both supervised unsupervised learning Hence, C-BIR technique evolved overcoming above stated concerns. this manuscript introduces two different techniques using support vector machine (SVM) logic-based approach classification. These on classification based feature extraction, region Interest (ROI), corner detection, similarity matching. proposed has been analyzed accuracy. outcomes study enhance performances than C-BIR.