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...

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Vydané v:	Biomedical engineering online Ročník 17; číslo 1; s. 63 - 19
Hlavní autori:	Wang, Changmiao, Elazab, Ahmed, Jia, Fucang, Wu, Jianhuang, Hu, Qingmao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 23.05.2018 BioMed Central Ltd Springer Nature B.V BMC
Predmet:	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
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