Automatic tissue characterization of air trapping in chest radiographs using deep neural networks

Significant progress has been made in recent years for computer-aided diagnosis of abnormal pulmonary textures from computed tomography (CT) images. Similar initiatives in chest radiographs (CXR), the common modality for pulmonary diagnosis, are much less developed. CXR are fast, cost effective and...

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Bibliographic Details

Published in:	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2016; pp. 97 - 100
Main Authors:	Mansoor, Awais, Perez, Geovanny, Nino, Gustavo, Linguraru, Marius George
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01.08.2016
Subjects:	Air Charge carrier processes Computed tomography Diagnosis, Computer-Assisted Humans Image Processing, Computer-Assisted - methods Lung - diagnostic imaging Lungs Machine learning Neural Networks, Computer Radiography, Thoracic - methods Shape Training Virus Diseases - diagnostic imaging Visualization
ISSN:	1557-170X, 2694-0604, 2694-0604
Online Access:	Get full text
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