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Computer-aided detection of pulmonary pathology in pediatric chest radiographs.

Author information

1
MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, South Africa.

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.

PMID:
20879452
DOI:
10.1007/978-3-642-15711-0_77
[Indexed for MEDLINE]

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