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Proceedings Paper

Automatic spatiotemporal matching of detected pleural thickenings
Author(s): Kraisorn Chaisaowong; Simon Kai Keller; Thomas Kraus
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Paper Abstract

Pleural thickenings can be found in asbestos exposed patient’s lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

Paper Details

Date Published: 10 January 2014
PDF: 5 pages
Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90691L (10 January 2014); doi: 10.1117/12.2049938
Show Author Affiliations
Kraisorn Chaisaowong, RWTH Aachen Univ. (Germany)
King Mongkut's Univ. of Technology North Bangkok (Thailand)
Simon Kai Keller, RWTH Aachen Univ. (Germany)
Thomas Kraus, Univ. Hospital Aachen (Germany)

Published in SPIE Proceedings Vol. 9069:
Fifth International Conference on Graphic and Image Processing (ICGIP 2013)
Yulin Wang; Xudong Jiang; Ming Yang; David Zhang; Xie Yi, Editor(s)

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