Medical X-Rays Categorization and Irregularity Recognition of Bone and Diagnosis of Bone disorders Based on Xception Model

Abstract

This study adopted a hybrid classification method for determining bone kinds and identifying bone deformities. The proposed methodology perceives the shoulder bones, forearm, humerus, elbow, hand, finger, leg, wrist,and knee. For this study, the Xception pre-trained model is used. The single-view and multi-view techniques are the two techniques used during the testing phase. The improved images send to first stage, which classifies them into the one of nine categories: shoulder, humerus, forearm, elbow, wrist, hand, finger, leg,and knee. Following categorization, the bones are input to second stage, that determines whether bones are normal or pathological. The MURA dataset is used for the experiments. Furthermore, the SVM layer or the classifier replaces the final layer of the used model. The results show that the SVM layer is superior. The study suggests the detection of normal and abnormal bone xrays. Determining whether the bone is normal or abnormal. If abnormal, include symptoms, diagnosis, and home remedies.