Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Anomaly Detection of Arm X-Ray Based on Deep Learning
3
Zitationen
1
Autoren
2020
Jahr
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.
Ähnliche Arbeiten
New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
2008 · 28.945 Zit.
TNM Classification of Malignant Tumours
1987 · 16.123 Zit.
A survey on deep learning in medical image analysis
2017 · 13.632 Zit.
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
2011 · 10.780 Zit.
The American Joint Committee on Cancer: the 7th Edition of the AJCC Cancer Staging Manual and the Future of TNM
2010 · 9.111 Zit.