Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder

Objective In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, high accuracy of diagnosis by an automated system can...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Biomedical engineering online Jg. 17; H. 1; S. 63 - 19
Hauptverfasser:	Wang, Changmiao, Elazab, Ahmed, Jia, Fucang, Wu, Jianhuang, Hu, Qingmao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 23.05.2018 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Accuracy Advances in Medical Robotics and Automation for Surgery and Rehabilitation Artificial intelligence Autoencoder Automation Biomaterials Biomedical Engineering and Bioengineering Biomedical Engineering/Biotechnology Biotechnology Care and treatment Chest Chest screening Chest x-rays Classification Computer aided diagnosis Datasets Deep learning Diagnosis Engineering Health screening Humans Image Processing, Computer-Assisted - methods Information processing International conferences Lesions Lung - diagnostic imaging Lung diseases Machine Learning Medical imaging Methods Neural networks Noise reduction Pattern recognition Radiography, Thoracic Radiology Receiver operating characteristic Reconstruction Regulatory approval ROC Curve Screening Signal-To-Noise Ratio Transfer learning Triage - methods X-rays China Deep learning Computer aided diagnosis Receiver operating characteristic Autoencoder Chest screening
ISSN:	1475-925X, 1475-925X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!