@inproceedings{Groeller_2016_P6, title = "PorosityAnalyzer: Visual Analysis and Evaluation of Segmentation Pipelines to Determine the Porosity in Fiber-Reinforced Polymers", author = "Johannes Weissenb\"{o}ck and Artem Amirkhanov and Eduard Gr\"{o}ller and Johannes Kastner and Christoph Heinzl", year = "2016", abstract = "In this paper we present PorosityAnalyzer, a novel tool for detailed evaluation and visual analysis of pore segmentation pipelines to determine the porosity in fiber-reinforced polymers (FRPs). The presented tool consists of two modules: the computation module and the analysis module. The computation module enables a convenient setup and execution of distributed off-line-computations on industrial 3D X-ray computed tomography datasets. It allows the user to assemble individual segmentation pipelines in the form of single pipeline steps, and to specify the parameter ranges as well as the sampling of the parameter-space of each pipeline segment. The result of a single segmentation run consists of the input parameters, the calculated 3D binary-segmentation mask, the resulting porosity value, and other derived results (e.g., segmentation pipeline runtime). The analysis module presents the data at different levels of detail by drill-down filtering in order to determine accurate and robust segmentation pipelines. Overview visualizations allow to initially compare and evaluate the segmentation pipelines. With a scatter plot matrix (SPLOM), the segmentation pipelines are examined in more detail based on their input and output parameters. Individual segmentation-pipeline runs are selected in the SPLOM and visually examined and compared in 2D slice views and 3D renderings by using aggregated segmentation masks and statistical contour renderings. PorosityAnalyzer has been thoroughly evaluated with the help of twelve domain experts. Two case studies demonstrate the applicability of our proposed concepts and visualization techniques, and show that our tool helps domain experts to gain new insights and improve their workflow efficiency.", month = oct, publisher = "IEEE Computer Society", booktitle = "IEEE Conference on Visual Analytics Science and Technology, 2016 (VAST 2016)", pages = "101--110", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/", } @article{Groeller_2016_P1, title = " Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests", author = "Aleksandr Amirkhanov and Artem Amirkhanov and Dietmar Salaberger and Johannes Kastner and Eduard Gr\"{o}ller and Christoph Heinzl", year = "2016", abstract = "Material engineers use interrupted in situ tensile testing to investigate the damage mechanisms in composite materials. For each subsequent scan, the load is incrementally increased until the specimen is completely fractured. During the interrupted in situ testing of glass fiber reinforced polymers (GFRPs) defects of four types are expected to appear: matrix fracture, fiber/matrix debonding, fiber pull-out, and fiber fracture. There is a growing demand for the detection and analysis of these defects among the material engineers. In this paper, we present a novel workflow for the detection, classification, and visual analysis of defects in GFRPs using interrupted in situ tensile tests in combination with X-ray Computed Tomography. The workflow is based on the automatic extraction of defects and fibers. We introduce the automatic Defect Classifier assigning the most suitable type to each defect based on its geometrical features. We present a visual analysis system that integrates four visualization methods: 1) the Defect Viewer highlights defects with visually encoded type in the context of the original CT image, 2) the Defect Density Maps provide an overview of the defect distributions according to type in 2D and 3D, 3) the Final Fracture Surface estimates the material fracture’s location and displays it as a 3D surface, 4) the 3D Magic Lens enables interactive exploration by combining detailed visualizations in the region of interest with overview visualizations as context. In collaboration with material engineers, we evaluate our solution and demonstrate its practical applicability.", journal = "Computer Graphics Forum (2016)", volume = " 35", number = "3", issn = "doi: 10.1111/cgf.12896", pages = "201--210", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/", } @article{Froehler_Berhnard_2015_ESM, title = "Multimodal Visualization and Analysis of Spectral and XCT Data", author = "Bernhard Fr\"{o}hler and Artem Amirkhanov and Johann Kastner and Eduard Gr\"{o}ller and Christoph Heinzl", year = "2015", abstract = "An increasing number of industrial applications demand a comprehensive analysis of both structural and chemical composition. Typically, non-destructive testing techniques focus on either structural or chemical characterization but do not deliver both. 3D X-Ray Computed Tomography (XCT) scans are well-suited for determining the internal and external structure of an object at high resolution. The attenuation value it delivers can however be the same or very similar for different materials. For a detailed chemical analysis XCT is therefore combined with spectral characterization techniques such as K-Edge Absorptiometry or X-ray Fluorescence Spectroscopy. In this paper, we are extending a previously introduced framework for visualization and analysis of specimens scanned with these two modalities in multiple ways: For better understanding the dependencies between the spectral energy levels, we propose Spectral Similarity Maps. Spectral Functional Boxplots visualize the statistical distribution of the spectral data. The Spectrum Explor-er improves the analysis of specimens of unknown composition. We demonstrate the usefulness of our techniques on several use cases.", month = apr, journal = "Computer Graphic Forum", volume = "33", number = "3", note = "appeared in June 2014", issn = "2411-5428", pages = "91--100", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Froehler_Berhnard_2015_ESM/", } @article{amirkhanov-2014-ama, title = "InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data", author = "Artem Amirkhanov and Bernhard Fr\"{o}hler and Johann Kastner and Eduard Gr\"{o}ller and Christoph Heinzl", year = "2014", abstract = "This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high-resolution X-ray computed tomography (XCT) for structural characterization and low-resolution X-ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non-spatial information to provide insight into an industrial component’s structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie-chart glyphs show elemental composition in 2D slice-views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie-chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real-world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided.", month = jun, journal = "Computer Graphics Forum", volume = "33", number = "3", note = "Article first published online: 12 JUL 2014", pages = "91--100", keywords = "multi-modal data, XRF, industrial computed tomography, linked views, spectral data", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/amirkhanov-2014-ama/", } @inproceedings{weissenboeck-2014, title = "FiberScout: An Interactive Tool for Exploring and Analyzing Fiber Reinforced Polymers", author = "Johannes Weissenb\"{o}ck and Artem Amirkhanov and Weimin Li and Andreas Reh and Aleksandr Amirkhanov and Eduard Gr\"{o}ller and Johann Kastner and Christoph Heinzl", year = "2014", abstract = "Advanced composites such as fiber reinforced polymers are promising candidate materials for future components as they allow integrating the continuously rising demands of industry regarding costeffectiveness, function-orientation, integration and weight. The most important structures of fiber reinforced polymers are the individual fibers, as their characteristics (stiffness, strength, ductility, durability, etc.) to a large extent determine the properties of the final component. The main contribution of this paper is the introduction of a new system for interactive exploration and visual analysis of fiber properties in X-ray computed tomography data of fiber reinforced polymers. The presented tool uses parallel coordinates to define and configure initial fiber classes. Using a scatter plot matrix linked to the parallel coordinates the initial classification may be refined. This allows to analyze hidden relationships between individual fiber properties. 2D and 3D views depict the resulting fiber classifications. By using polar plots an intuitive rendering of the fiber orientation distribution is provided. In addition, two modules of higher abstraction are proposed: The Blob visualization creates a hull around fibers with similar characteristics. The fiber metadata visualization allows to calculate overlays for 2D and 3D views containing regional information of particular material characteristics. The proposed system has been evaluated by two groups of domain experts. Applying the presented concepts the user feedback shows that the domain experts are now able to efficiently perform tasks as classification of fibers, visualization of fiber lengths and orientations, and visualization of fiber regions. The insights gained can be forwarded to the design office as well as to material development and simulation, in order to speed up the development of novel composite components.", month = mar, isbn = "978-1-4799-2874-3 ", publisher = "IEEE Computer Society", location = "Yokohama", booktitle = "Proceedings of 2014 IEEE Pacific Visualization Symposium (PacificVis) (2014)", pages = "153--160", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/weissenboeck-2014/", } @inproceedings{Groeller_Eduard_2014_UCT, title = "Uncertainty in CT Metrology: Visualizations for Exploration and Analysis of Geometric Tolerances", author = "Artem Amirkhanov and Bernhard Fr\"{o}hler and Michael Reiter and Johann Kastner and Eduard Gr\"{o}ller and Christoph Heinzl", year = "2014", abstract = "Industrial 3D X-ray computed tomography (3DXCT) is increasingly applied as a technique for metrology applications. In contrast to comventional metrology tools such as coordinate measurement machines (CMMs). 3DXCT only estimates the exact position of the specimen’s surface and is subjected to a specific set of artifact types. These factors result in uncertainty that is present in the data. Previous work by Amirkhanov et. al [2] presented a tool prototype that is taking such uncertainty into account when measuring geometric tolerances such as straightness, circularity, or flatness. In this paper we extend the previous work with two more geometric tolerance types: cylindricity and angularity. We provide methods and tools for visualization, inspection, and analysis of these tolerances. For the cylindricity tolerance we employ neighboring profiles visualization, box-plot overview, and interactive 3D view. We evaluate applicability and usefulness our methods on a new TP03 data set, and present results and new potential use cases.", month = feb, location = "Wels, Austria", issn = "978-3-8440-2557-6", event = "iCT Conference 2014", booktitle = "Proceedings of 5th Conference on Industrial Computed Tomography (iCT Conference 2014)", journal = "Proceedings of iCT 2014", pages = "189--195", keywords = "metrology, level-of-details, uncertainty visualization, Industrial 3D computed tomography", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/Groeller_Eduard_2014_UCT/", } @incollection{Groeller_Eduard_2014_THS, title = "The Haunted Swamps of Heuristics: Uncertainty in Problem Solving", author = "Artem Amirkhanov and Stefan Bruckner and Christoph Heinzl and Eduard Gr\"{o}ller", year = "2014", abstract = "In scientific visualization the key task of research is the provision of insight into a problem. Finding the solution to a problem may be seen as finding a path through some rugged terrain which contains mountains, chasms, swamps, and few flatlands. This path—an algorithm discovered by the researcher—helps users to easily move around this unknown area. If this way is a wide road paved with stones it will be used for a long time by many travelers. However, a narrow footpath leading through deep forests and deadly swamps will attract only a few adventure seekers. There are many different paths with different levels of comfort, length, and stability, which are uncertain during the research process. Finding a systematic way to deal with this uncertainty can greatly assist the search for a safe path which is in our case the development of a suitable visualization algorithm for a specific problem. In this work we will analyze the sources of uncertainty in heuristically solving visualization problems and will propose directions to handle these uncertainties.", booktitle = "Scientific Visualization", chapter = "Uncertainty, Multifield, Biomedical, and Scalable Visualization", editor = "Charles D. Hansen, Min Chen, Christopher R. Johnson, Arie E. Kaufman, Hans Hagen", isbn = "978-1-4471-6496-8", note = "Chapter 5", publisher = "Springer London", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/Groeller_Eduard_2014_THS/", } @inproceedings{amirkhanov_2013_AMA, title = "Fuzzy CT Metrology: Dimensional Measurements on Uncertain Data", author = "Artem Amirkhanov and Christoph Heinzl and Christoph Kuhn and Johann Kastner and Eduard Gr\"{o}ller", year = "2013", abstract = "Metrology through geometric dimensioning and tolerancing is an important instrument applied for industrial manufacturing and quality control. Typically tactile or optical coordinate measurement machines (CMMs) are used to perform dimensional measurements. In recent years industrial 3D X-ray computed tomography (3DXCT) has been increasingly applied for metrology due to the development of XCT systems with higher accuracy and their ability to capture both internal and external structures of a specimen within one scan. Using 3DXCT the location of the specimen surface is estimated based on the scanned attenuation coefficients. As opposed to tactile or optical measurement techniques, the surface is not explicit and implies a certain positional uncertainty depending on artifacts and noise in the scan data and the used surface extraction algorithm. Moreover, conventional XCT measurement software does not consider uncertainty in the data. In this work we present techniques which account for uncertainty arising in the XCT metrology data flow. Our technique provides the domain experts with uncertainty visualizations, which extend the XCT metrology workflow on different levels. The developed techniques are integrated into a tool utilizing linked views, smart 3D tolerance tagging and plotting functionalities. The presented system is capable of visualizing the uncertainty of measurements on various levels-of-detail. Commonly known geometric tolerance indications are provided as smart tolerance tags. Finally, we incorporate the uncertainty of the data as a context in commonly used measurement plots. The proposed techniques provide an augmented insight into the reliability of geometric tolerances while maintaining the daily workflow of domain specialists, giving the user additional information on the nature of areas with high uncertainty. The presented techniques are evaluated based on domain experts feedback in collaboration with our company partners.", month = may, isbn = "978-80-223-3377-1", publisher = "Comenius university, Bratislava, Slovakia", location = "Smolenice, Slovak Republic", booktitle = "SCCG 2013 - 29th Proceedings Spring conference on Computer Graphics", pages = "93--101", keywords = "metrology, uncertainty visualization, level-of-details, industrial 3D computed tomography", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/amirkhanov_2013_AMA/", } @phdthesis{amirkhanov-2012-thesis, title = "Visualization of Industrial 3DXCT Data", author = "Artem Amirkhanov", year = "2012", abstract = "Three-dimensional X-ray computed tomography (3DXCT) is a powerful technique for generating a digital 3D volumetric representation of a specimen from a series of 2D X-ray penetration images. The main advantage of 3DXCT is its ability to detect both the interior and the exterior structure of a specimen in one single scan. Having been used in medical diagnostics for a long time, 3DXCT is increasingly employed in industry as a method for nondestructive testing and quality control. One especially challenging industrial application is metrology, which has to fulfill the demands of today’s standards in industrial quality control. 3DXCT facilitates dimensional measurements of internal structures and of inaccessible parts of a component. However the successful industrial application of 3DXCT is constrained by a set of major problems: Artifacts: Industrial 3DXCT systems face problems due to various types of artifacts. The appearance of artifacts in the 3DXCT scan data distorts its correlation to the actual evaluated industrial object and can lead to errors in measurements and false analysis results. Some types of artifacts are affected by the placement of a specimen in the scanning device. Multi-material components: Another problem is occurring when multi-material components (MMCs) are inspected using industrial 3DXCT. Common industrial MMCs may contain metal parts surrounded by plastic materials. A major problem of this type of components is the presence of metal-caused streaking artifacts and distortions. They are located around metal components and significantly influence the material characterization. Furthermore these streaking artefacts and distortions may even prevent any further analysis (especially for the plastic components). Measurements uncertainty: If metrology using 3DXCT is performed, the location of the specimen surface is estimated using the reconstructed 3D volume data. As opposed to mechanical or optical measurement techniques, the surface is not explicit and has a particular positional uncertainty depending on the artifacts and noise in the scan data and the surface extraction algorithm. Conventional CT metrology software does not account for the uncertainty of the data. This thesis is devoted to the development of techniques overcoming the aforementioned problems of common industrial tasks involving the usage of 3DXCT for nondestructive testing and quality control with a main focus on industrial 3DXCT metrology. Several novel contributions utilizing visualization techniques and visual analysis methods were implemented in integrated tools assisting typical industrial 3DXCT tasks during different stages of the data pipeline.", month = nov, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2012/amirkhanov-2012-thesis/", } @article{amirkhanov-2011, title = "Projection-Based Metal-Artifact Reduction for Industrial 3D X-ray Computed Tomography", author = "Artem Amirkhanov and Christoph Heinzl and Michael Reiter and Johann Kastner and Eduard Gr\"{o}ller", year = "2011", abstract = "Multi-material components, which contain metal parts surrounded by plastic materials, are highly interesting for inspection using industrial 3D X-ray computed tomography (3DXCT). Examples of this application scenario are connectors or housings with metal inlays in the electronic or automotive industry. A major problem of this type of components is the presence of metal, which causes streaking artifacts and distorts the surrounding media in the reconstructed volume. Streaking artifacts and dark-band artifacts around metal components significantly influence the material characterization (especially for the plastic components). In specific cases these artifacts even prevent a further analysis. Due to the nature and the different characteristics of artifacts, the development of an efficient artifact-reduction technique in reconstruction-space is rather complicated. In this paper we present a projection-space pipeline for metal-artifacts reduction. The proposed technique first segments the metal in the spatial domain of the reconstructed volume in order to separate it from the other materials. Then metal parts are forward-projected on the set of projections in a way that metal-projection regions are treated as voids. Subsequently the voids, which are left by the removed metal, are interpolated in the 2D projections. Finally, the metal is inserted back into the reconstructed 3D volume during the fusion stage. We present a visual analysis tool, allowing for interactive parameter estimation of the metal segmentation. The results of the proposed artifact-reduction technique are demonstrated on a test part as well as on real world components. For these specimens we achieve a significant reduction of metal artifacts, allowing an enhanced material characterization.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "17", number = "12", issn = "1077-2626", pages = "2193--2202", keywords = "Metal-artifact reduction, multi-material components, 3D X-ray computed tomography, visual analysis", URL = "https://www.cg.tuwien.ac.at/research/publications/2011/amirkhanov-2011/", } @article{amirkhanov2010AMA, title = "Visual Optimality and Stability Analysis of 3DCT Scan Positions", author = "Artem Amirkhanov and Christoph Heinzl and Michael Reiter and Eduard Gr\"{o}ller", year = "2010", abstract = "Industrial cone-beam X-Ray computed tomography (CT) systems often face problems due to artifacts caused by a bad placement of the specimen on the rotary plate. This paper presents a visual-analysis tool for CT systems, which provides a simulation-based preview and estimates artifacts and deviations of a specimen’s placement using the corresponding 3D geometrical surface model as input. The presented tool identifies potentially good or bad placements of a specimen and regions of a specimen, which cause the major portion of artefacts. The tool can be used for a preliminary analysis of the specimen before CT scanning, in order to determine the optimal way of placing the object. The analysis includes: penetration lengths, placement stability and an investigation in Radon space. Novel visualization techniques are applied to the simulation data. A stability widget is presented for determining the placement parameters’ robustness. The performance and the comparison of results provided by the tool compared with real world data is demonstrated using two specimens.", month = oct, journal = "IEEE Transactions on Visualization and Computer Graphics", pages = "Page 1477 --1487", URL = "https://www.cg.tuwien.ac.at/research/publications/2010/amirkhanov2010AMA/", }