Bone osteosarcoma tumor classification

Osteosarcoma is a malignant bone tumor that usually affects children and adolescents. Early detection of osteosarcoma tumors increases the likelihood successful therapy. Manual identification requires highly skilled doctors. In this study, we attempt to create model automatically diagnose into three categories; non-tumor, viable-tumor, tumor. The suggested methodology can help medical professionals identify correctly quickly. proposed approach uses gray level co-occurrence matrix (GLCM) extract features for feature extraction different classifiers detection. used classifier are XG-Boost, support vector machine (SVM), K-nearest neighbors. Finally, ensemble voting by combining predictions from these classifiers. system achieves 91.8% accuracy.