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International Journal of Computer Assisted Radiology and Surgery

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01.09.2016 | Original Article

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

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

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 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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Titel: Edge map analysis in chest X-rays for automatic pulmonary abnormality screening
verfasst von: K. C. Santosh
Szilárd Vajda
Sameer Antani
George R. Thoma
Publikationsdatum: 01.09.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 9/2016
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-016-1359-6

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

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