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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Vydané v:	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Ročník 2016; s. 97 - 100
Hlavní autori:	Mansoor, Awais, Perez, Geovanny, Nino, Gustavo, Linguraru, Marius George
Médium:	Konferenčný príspevok.. Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.08.2016
Predmet:	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
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