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Proceedings Paper

Automatic heart localization and radiographic index computation in chest x-rays
Author(s): Sema Candemir; Stefan Jaeger; Wilson Lin; Zhiyun Xue; Sameer Antani; George Thoma
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Paper Abstract

This study proposes a novel automated method for cardiomegaly detection in chest X-rays (CXRs). The algo- rithm has two main stages: i) heart and lung region localization on CXRs, and ii) radiographic index extraction from the heart and lung boundaries. We employed a lung detection algorithm and extended it to automatically compute the heart boundaries. The typical models of heart and lung regions are learned using a public CXR dataset with boundary markings. The method estimates the location of these regions in candidate ('patient') CXR images by registering models to the patient CXR. For the radiographic index computation, we implemented the traditional and recently published indexes in the literature. The method is tested on a database with 250 abnormal, and 250 normal CXRs. The radiographic indexes are combined through a classifier, and the method successfully classifies the patients with cardiomegaly with a 0:77 accuracy, 0:77 sensitivity and 0:76 specificity.

Paper Details

Date Published: 24 March 2016
PDF: 8 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978517 (24 March 2016); doi: 10.1117/12.2217209
Show Author Affiliations
Sema Candemir, National Library of Medicine (United States)
Stefan Jaeger, National Library of Medicine (United States)
Wilson Lin, National Library of Medicine (United States)
Zhiyun Xue, National Library of Medicine (United States)
Sameer Antani, National Library of Medicine (United States)
George Thoma, National Library of Medicine (United States)


Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato, Editor(s)

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