@inproceedings{FroehlerdaCunhaMeloWeissenboecketal., author = {Fr{\"o}hler, Bernhard and da Cunha Melo, Lucas and Weissenb{\"o}ck, Johannes and Kastner, Johann and M{\"o}ller, Torsten and Hege, Hans-Christian and Gr{\"o}ller, Eduard M. and Sanctorum, Jonathan and De Beenhouwer, Jan and Sijbers, Jan and Heinzl, Christoph}, title = {Tools for the analysis of datasets from X-ray computed tomography based on Talbot-Lau grating interferometry}, series = {Proceedings of iCT 2019, (9th Conference on Industrial Computed Tomography, Padova, Italy - iCT 2019, February 13-15, 2019)}, booktitle = {Proceedings of iCT 2019, (9th Conference on Industrial Computed Tomography, Padova, Italy - iCT 2019, February 13-15, 2019)}, number = {paper 52}, pages = {8}, 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 modal- ities. 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.}, language = {en} }