Automatic spatiotemporal matching of detected pleural thickenings

Kraisorn Chaisaowong; Simon Kai Keller; Thomas Kraus

doi:10.1117/12.2049938

10 January 2014 Automatic spatiotemporal matching of detected pleural thickenings

Kraisorn Chaisaowong, Simon Kai Keller, Thomas Kraus

Proceedings Volume 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013); 90691L (2014) https://doi.org/10.1117/12.2049938
Event: Fifth International Conference on Graphic and Image Processing, 2013, Hong Kong, China

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%).

Citation Download Citation

Kraisorn Chaisaowong, Simon Kai Keller, and Thomas Kraus "Automatic spatiotemporal matching of detected pleural thickenings", Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90691L (10 January 2014); https://doi.org/10.1117/12.2049938

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