| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Gall, Alexander
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (3/3 displayed)
- 2024Unsupervised Segmentation of Industrial X-ray Computed Tomography Data with the Segment Anything Modelcitations
- 2020Immersive analytics of multidimensional volumetric data
- 2017The New Xpert MTB/RIF Ultra: Improving Detection of <i>Mycobacterium tuberculosis</i> and Resistance to Rifampin in an Assay Suitable for Point-of-Care Testingcitations
Places of action
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thesis
Immersive analytics of multidimensional volumetric data
Abstract
Understanding and interpreting volumetric multidimensional data is a complex and cognitively demanding task. Especially in the field of material science the exploration of large spatial data is crucial. Non-destructive testing (NDT) plays an essential role in industrial production, especially in the field of material and component testing, regarding the analysis, visualization, and optimization of new, highly complex material systems such as fiber composites. In order to support the increasing demands on these materials and components of the future in industrial applications, extensive inspections and controls are essential. NDT inspection data generated by imaging techniques such as X-ray computed tomography (XCT) include 2D images, volumetric models, and derived high-dimensional data spaces. They can rarely, or only to a limited extent, be evaluated on desktop monitors using standard 2D visualization techniques. Therefore, novel immersive visualization and interaction techniques using Virtual Reality (VR) were developed in this thesis to investigate highly complex, heterogeneous material systems. We present a novel technique called "Model in Miniature" for an effective and interactive exploration and visual analysis of fiber characteristics. Furthermore, we combine different approaches like exploded views, histograms, and node-link diagrams to provide unique insights into the composite materials. Using embodied interaction and navigation, and enhancing the user's abilities, previously impossible insights into the most complex material structures are possible. We use the latest findings from the field of Immersive Analytics to make the spatial data more comprehensible and test the results in a qualitative study with domain experts. The evaluation of our techniques has shown positive results, which indicate the benefits of an immersive analysis of composite materials and the exploration of overall high-dimensional volumes. The insights gained therefore represent an important step towards the further development of future immersive analysis platforms.