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2017 | OriginalPaper | Chapter

Circular Foreign Object Detection in Chest X-ray Images

Authors : Fatema Tuz Zohora, K. C. Santosh

Published in: Recent Trends in Image Processing and Pattern Recognition

Publisher: Springer Singapore

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Abstract

In automated chest X-ray screening (to detect i.e., Tuberculosis for instance), the presence of foreign objects (buttons, medical devices) hinders it’s performance. In this paper, we present a new technique for detecting circular foreign objects, in particular buttons, within chest X-ray (CXR) images. In our technique, we use a pre-processing step that enhances the CXRs. Using these enhanced images, we find the edge images performing four different edge detection algorithms (Sobel, Canny, Prewitt, and Roberts) and after that, we apply some morphological operations to select candidates (image segmentation) in the chest region. Finally, we apply circular Hough transform (CHT) to detect the circular foreign objects on those images. In all tests, our algorithm performed well under a variety of CXRs. We also compared our proposed technique’s performance with existing techniques in literature (Viola-Jones and CHT). Our technique was able to excel performance in terms of both detection accuracy and computational time.

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Footnotes
1
Note that, we have tested using 50 CXR images.
 
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Metadata
Title
Circular Foreign Object Detection in Chest X-ray Images
Authors
Fatema Tuz Zohora
K. C. Santosh
Copyright Year
2017
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-4859-3_35

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