Computer-aided detection of pulmonary pathology in pediatric chest radiographs
Date
2010
Authors
Mouton A.
Pitcher R.D.
Douglas T.S.
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
A scheme for triaging pulmonary abnormalities in pediatric chest radiographs for specialist interpretation would be useful in resource-poor settings, especially those with a high tuberculosis burden. We assess computer-aided detection of pulmonary pathology in pediatric digital chest X-ray images. The method comprises four phases suggested in the literature: lung field segmentation, lung field subdivision, feature extraction and classification. The output of the system is a probability map for each image, giving an indication of the degree of abnormality of every region in the lung fields; the maps may be used as a visual tool for identifying those cases that need further attention. The system is evaluated on a set of anterior-posterior chest images obtained using a linear slot-scanning digital X-ray machine. The classification results produced an area under the ROC of 0.782, averaged over all regions. © 2010 Springer-Verlag.
Description
Keywords
Anterior posteriors, Chest image, Chest radiographs, Chest X-ray image, classification, Classification results, Computer-aided detection, Feature extraction and classification, Lung field segmentation, Lung fields, Probability maps, pulmonary abnormality, tuberculosis, Visual tools, X ray machine, Biological organs, Diseases, Feature extraction, Mammography, Medical computing, Medical imaging, Pathology, Pediatrics, Radiography, Computer aided diagnosis
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6363 LNCS
PART 3
6363 LNCS
PART 3