Anomaly Detection of Arm X-Ray Based on Deep Learning. Issue 4 (February 2020)

• Record Type: Journal Article
• Authors: Wang, Jingchen
• Is Part Of: IOP conference series. Volume 440:Issue 4(2020)
• Publication Date: 2020-02
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/440/4/042056
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: The goal of this paper is to determine whether the arm has a fracture by detecting the X-ray of the human arm. This paper used the Keras deep learning framework and use the NASNetMobile model for training. The data set is MURA-v1.1, and the test accuracy on the verification set is about 70%. After downloading X-ray photographs of fractured arms, this paper performed an anomaly detection of the single image to test the accuracy of the model.