Paper
24 March 2016 Automatic heart localization and radiographic index computation in chest x-rays
Author Affiliations +
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sema Candemir, Stefan Jaeger, Wilson Lin, Zhiyun Xue, Sameer Antani, and George Thoma "Automatic heart localization and radiographic index computation in chest x-rays", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978517 (24 March 2016); https://doi.org/10.1117/12.2217209
Lens.org Logo
CITATIONS
Cited by 13 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Heart

Lung

Chest imaging

X-rays

Image segmentation

Detection and tracking algorithms

Medicine

Back to Top