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NDT.net Issue - 2019-03 - Articles
NDT.net Issue: 2019-03
Publication: 9th Conference on Industrial Computed Tomography (iCT) 2019, 13-15 Feb, Padova, Italy (iCT 2019)
Session: Short talks
Thu 13:50 Auditorium
ARTICLE

Tools for the Analysis of Datasets from X-Ray Computed Tomography based on Talbot-Lau Grating Interferometry

Bernhard Fröhler16, Lucas Da Cunha Melo22, Johannes Weissenböck111, Johann Kastner1120, Torsten Möller32, Hans-Christian Hege4, Eduard Gröller211, Jonathan Sanctorum53, Jan De Beenhouwer515, Jan Sijbers518, Christoph Heinzl138
1Research Group Computed Tomography; Upper Austrian University of Applied Sciences (FH OÖ)166, Wels, Austria
2VRVis Research Center; Vienna University of Technolog (TU)57, Vienna, Austria
3Faculty of Computer Science; University of Vienna4, Vienna, Austria
4Konrad-Zuse-Institut Berlin (ZIB)19, Berlin, Germany
5University of Antwerpen34, Antwerpen, Belgium

Abstract: This work introduces methods for analyzing the three imaging modalities delivered by Talbot-Lau grating interferometry X-ray computed tomography (TLGI-XCT). The first problem we address is providing a quick way to show a fusion of all three modalities. For this purpose the tri-modal transfer function widget is introduced. The widget controls a mixing function that uses the output of the transfer functions of all three modalities, allowing the user to create one customized fused image. A second problem prevalent in processing TLGI-XCT data is a lack of tools for analyzing the segmentation process of such multimodal data. We address this by providing methods for computing three types of uncertainty: From probabilistic segmentation algorithms, from the voxel neighborhoods as well as from a collection of results. We furthermore introduce a linked views interface to explore this data. The techniques are evaluated on a TLGI-XCT scan of a carbon-fiber reinforced dataset with impact damage. We show that the transfer function widget accelerates and facilitates the exploration of this dataset, while the uncertainty analysis methods give insights into how to tweak and improve segmentation algorithms for more suitable results.

Keywords: Radiographic Testing (RT) (1523), Other Methods (1114), image fusion (3), multimodal data (1), transfer function design (1), image segmentation uncertainty (1),
*Keywords are freely formed keywords from the authors and thus you may Search also for similar terms.

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