@inproceedings{c7ac9913e8d346998173ef001c3c3edf,
title = "Fully automatic removal of chest tube figures from postero-anterior chest radiographs",
abstract = "The presence of artificial objects in radiographic images is common. For example, 33% of chest radiographs contain catheters. Anomaly detection algorithms used to monitor disease progression should not be confused by artificial objects such as catheters, chest tubes, pacemakers or even cloths that might be present in chest radiographs. Hence, the detection and the removal of artificial objects via a preprocessing module are very useful for Computer Aided Diagnosis (CAD) research. In this paper, we propose a Convolutional Neural Network (CNN) architecture that works as a trainable filter that removes simulated chest tube figures from chest radiographs.",
keywords = "Artificial object, Chest radiography, Chest tube, Computer aided diagnosis (CAD), Convolutional neural network (CNN), Figure removing",
author = "Mercan, {C. Ahmet} and Celebi, {M. Serdar}",
year = "2010",
doi = "10.2316/p.2010.679-041",
language = "English",
isbn = "9780889868243",
series = "Proceedings of the 11th IASTED International Conference on Computer Graphics and Imaging, CGIM 2010",
publisher = "Acta Press",
pages = "298--302",
booktitle = "Proceedings of the 11th IASTED International Conference on Computer Graphics and Imaging, CGIM 2010",
address = "Canada",
note = "11th IASTED International Conference on Computer Graphics and Imaging, CGIM 2010 ; Conference date: 17-02-2010 Through 19-02-2010",
}