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Published in: International Journal of Computer Assisted Radiology and Surgery 9/2016

01-09-2016 | Original Article

Edge map analysis in chest X-rays for automatic pulmonary abnormality screening

Authors: K. C. Santosh, Szilárd Vajda, Sameer Antani, George R. Thoma

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 9/2016

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Abstract

Purpose

Our particular motivator is the need for screening HIV+ populations in resource-constrained regions for the evidence of tuberculosis, using posteroanterior chest radiographs (CXRs).

Method

The proposed method is motivated by the observation that abnormal CXRs tend to exhibit corrupted and/or deformed thoracic edge maps. We study histograms of thoracic edges for all possible orientations of gradients in the range \([0, 2\pi )\) at different numbers of bins and different pyramid levels, using five different regions-of-interest selection.

Results

We have used two CXR benchmark collections made available by the U.S. National Library of Medicine and have achieved a maximum abnormality detection accuracy (ACC) of 86.36 % and area under the ROC curve (AUC) of 0.93 at 1 s per image, on average.

Conclusion

We have presented an automatic method for screening pulmonary abnormalities using thoracic edge map in CXR images. The proposed method outperforms previously reported state-of-the-art results.
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Metadata
Title
Edge map analysis in chest X-rays for automatic pulmonary abnormality screening
Authors
K. C. Santosh
Szilárd Vajda
Sameer Antani
George R. Thoma
Publication date
01-09-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Computer Assisted Radiology and Surgery / Issue 9/2016
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-016-1359-6

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