Publikationen

A Comparative Study of Supervised and Self-Supervised Denoising Techniques for Defect Segmentation in Industrial CT Imaging

V. Florian, J. Shi, W. Palestijn, D. Pelt, K. Batenburg, T. Lang, C. Heinzl, C. Kretzer, S. Kasperl, D. Wolfschläger and others, "A Comparative Study of Supervised and Self-Supervised Denoising Techniques for Defect Segmentation in Industrial CT Imaging" in 14th Conference on Industrial Computed Tomography (iCT) , 2025.

Degradation Detection in Rice Products via Shape Variations in XCT Simulation-Empowered AI

M. Yosifov, T. Lang, V. Florian, S. Gerth, J. Beenhouwer, J. Sijbers, J. Kastner and C. Heinzl, "Degradation Detection in Rice Products via Shape Variations in XCT Simulation-Empowered AI" , Journal of Nondestructive Evaluation , vol. 44, no. 1, pp. 10, 2025.

Exploring Large Quantities of Secondary Data from High-Resolution Synchrotron X-ray Computed Tomography Scans Using AccuStripes

A. Heim, T. Lang and C. Heinzl, "Exploring Large Quantities of Secondary Data from High-Resolution Synchrotron X-ray Computed Tomography Scans Using AccuStripes" , arXiv preprint arXiv:2505.10098 , 2025.

Immersive Inspection: Intuitive Material Analysis using X-Ray Computed Tomography Data in AR

A. Gall, A. Heim, P. Weinberger, B. Fröhler, J. Kastner and C. Heinzl, "Immersive Inspection: Intuitive Material Analysis using X-Ray Computed Tomography Data in AR" , Journal of Nondestructive Evaluation , vol. 44, no. 3, pp. 79, 2025.

Machine learning-supported visual analytics for high resolution X-ray inspection of metal matrix composites

T. Lang, A. Heim and C. Heinzl, "Machine learning-supported visual analytics for high resolution X-ray inspection of metal matrix composites" , Tomography of Materials and Structures , vol. 7, pp. 100047, 2025.

MARV: Multiview Augmented Reality Visualisation for Exploring Rich Material Data

A. Gall, A. Heim, E. Gröller and C. Heinzl, "MARV: Multiview Augmented Reality Visualisation for Exploring Rich Material Data" in Computer Graphics Forum , 2025. pp. e70150.

Quantifying the Impact of XCT Data Compression on Defect Shapes

T. Lang and C. Heinzl, "Quantifying the Impact of XCT Data Compression on Defect Shapes" in DIR 2025 , 2025. pp. 6.

Quantum Image Visualizer: Visual Debugging of Quantum Image Processing Circuits

A. Heim, T. Lang, A. Gall, E. Gröller and C. Heinzl, "Quantum Image Visualizer: Visual Debugging of Quantum Image Processing Circuits" , arXiv preprint arXiv:2504.09902 , 2025.

Superimposing Synthetic Defects into Real XCT Data and Segmentation-Based Comparison for Advanced Probability of Detection Evaluation

M. Yosifov, B. Fröhler, J. Sijbers, J. Beenhouwer, J. Kastner and C. Heinzl, "Superimposing Synthetic Defects into Real XCT Data and Segmentation-Based Comparison for Advanced Probability of Detection Evaluation" , Journal of Nondestructive Evaluation , vol. 44, no. 4, pp. 119, 2025.

AccuStripes: Visual exploration and comparison of univariate data distributions using color and binning

A. Heim, A. Gall, M. Waldner, E. Gröller and C. Heinzl, "AccuStripes: Visual exploration and comparison of univariate data distributions using color and binning" , Computers & Graphics , vol. 119, pp. 103906, 2024.

Advancing Visual Computing in Materials Science (Shonan Seminar 189)

C. Heinzl, R. G. Raidou, K. Potter, Y. Takeshima, M. Kirby and G. Requena, "Advancing Visual Computing in Materials Science (Shonan Seminar 189)" , arXiv preprint arXiv:2407.03355 , 2024.

Big Data Analytics for the Inspection of Battery Materials

T. Lang, A. Heim and C. Heinzl, "Big Data Analytics for the Inspection of Battery Materials" , eJ. Nondestruct. Test. , vol. 29, no. 3, 2024.

Immersive Analysis: Enhancing Material Inspection of X-Ray Computed Tomography Datasets in Augmented Reality

A. Gall, A. Heim, P. Weinberger, B. Fröhler, J. Kastner and C. Heinzl, "Immersive Analysis: Enhancing Material Inspection of X-Ray Computed Tomography Datasets in Augmented Reality" , arXiv preprint arXiv:2404.12751 , 2024.

MDD-Glyphs: Immersive Insights Through Multidimensional Distribution Glyphs

A. Gall, A. Heim, E. Gröller and C. Heinzl, "MDD-Glyphs: Immersive Insights Through Multidimensional Distribution Glyphs" , arXiv preprint arXiv:2404.14814 , 2024.

Volume conductor: interactive visibility management for crowded volumes

Lesar, R. Alharbi, C. Bohak, O. Strnad, C. Heinzl, M. Marolt and I. Viola, "Volume conductor: interactive visibility management for crowded volumes" , Visual Computer , 2024.

DOI: 10.1007/s00371-023-02828-8

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151340753&doi=10.1007%2fs00371-023-02828-8&partnerID=40&md5=c543f8a79f05cd9ff4664d6ed16eb5f9

Adaptive Volumetric Anatomy Visualization in VR with Tangible Control

C. Kleinbeck, M. Smietana, N. Lewis, T. Teufel, J. Kreimeier, C. Heinzl, J. Steiner, C. Anthes and D. Roth, "Adaptive Volumetric Anatomy Visualization in VR with Tangible Control" in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) , IEEE, 2023. pp. 613-614.

Cardiac Visualisation Along the RV-Continuum-A High-Fidelity Pilot Study

D. Aigner, N. Wang, D. Kielmayer, J. Steiner, J. Hochpöchler, C. Heinzl, D. Roth, F. Maurer and C. Anthes, "Cardiac Visualisation Along the RV-Continuum-A High-Fidelity Pilot Study" in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) , IEEE, 2023. pp. 675-680.

cuPARE: parametric reconstruction of curved fibres from glass fibre-reinforced composites

T. Elberfeld, B. Fröhler, C. Heinzl, J. Sijbers and J. Beenhouwer, "cuPARE: parametric reconstruction of curved fibres from glass fibre-reinforced composites" , Nondestructive Testing and Evaluation , vol. 38, no. 4, pp. 648-667, 2023.

DOI: 10.1080/10589759.2022.2155647

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145069174&doi=10.1080%2f10589759.2022.2155647&partnerID=40&md5=652ab5023dba2ff3c3733ae6db8bec12

Defect detectability analysis via probability of defect detection between traditional and deep learning methods in numerical simulations

M. Yosifov, P. Weinberger, M. Reiter, F. Bernhard, J. Beenhouwer, J. Sijbers, J. Kastner and C. Heinzl, "Defect detectability analysis via probability of defect detection between traditional and deep learning methods in numerical simulations" in iCT2023 , 2023. pp. 10.

NDTFlix: Collaborative Remote Analysis of X-ray Computed Tomography Datasets

C. H. Bernhard Fröhler, "NDTFlix: Collaborative Remote Analysis of X-ray Computed Tomography Datasets" in iCT2023 , 2023. pp. 7.

Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network

M. Yosifov, P. Weinberger, B. Plank, B. Fröhler, M. Hoeglinger, J. Kastner and C. Heinzl, "Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network" , Acta Polytechnica CTU Proceedings , vol. 42, pp. 87-93, 2023.

Uncertainty Unveiled: Revealing the Uncertainty of Distribution Visualization Through Cross Reality

A. Gall, A. Heim, B. Fröhler and C. Heinzl, "Uncertainty Unveiled: Revealing the Uncertainty of Distribution Visualization Through Cross Reality" in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) , IEEE, 2023. pp. 20-24.

A Survey on Cross-Virtuality Analytics

B. Fröhler, C. Anthes, F. Pointecker, J. Friedl, D. Schwajda, A. Riegler, S. Tripathi, C. Holzmann, M. Brunner, H. Jodlbauer, H. Jetter and C. Heinzl, "A Survey on Cross-Virtuality Analytics" , Computer Graphics Forum , vol. 41, no. 1, pp. 465-494, 2022.

DOI: 10.1111/cgf.14447

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124532986&doi=10.1111%2fcgf.14447&partnerID=40&md5=fef1d45913e0ceadf1d64ad3cd1507c9

AccuStripes: Adaptive Binning for the Visual Comparison of Univariate Data Distributions

A. Heim, E. Gröller and C. Heinzl, "AccuStripes: Adaptive Binning for the Visual Comparison of Univariate Data Distributions" , arXiv preprint arXiv:2207.13663 , 2022.

Cross-virtuality analysis of rich X-ray computed tomography data for materials science applications

A. Gall, B. Fröhler, J. Maurer, J. Kastner and C. Heinzl, "Cross-virtuality analysis of rich X-ray computed tomography data for materials science applications" , Nondestructive Testing and Evaluation , vol. 37, no. 5, pp. 566-581, 2022.

DOI: 10.1080/10589759.2022.2075864

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130980828&doi=10.1080%2f10589759.2022.2075864&partnerID=40&md5=779f0632730fea359cf8e9cfbc848904

Multiscale In-situ Investigations of the Formation of Delamination in CFRP by Means of X-Ray Micro-Computed Tomography

M. Höglinger, B. Plank, M. Thor, C. Heinzl and J. Kastner, "Multiscale In-situ Investigations of the Formation of Delamination in CFRP by Means of X-Ray Micro-Computed Tomography" in iCT2022 , 2022. pp. 5.

Probability of detection applied to X-ray inspection using numerical simulations

M. Yosifov, M. Reiter, S. Heupl, C. Gusenbauer, B. Fröhler, R. Fernández- Gutiérrez, J. De Beenhouwer, J. Sijbers, J. Kastner and C. Heinzl, "Probability of detection applied to X-ray inspection using numerical simulations" , Nondestructive Testing and Evaluation , vol. 37, no. 5, pp. 536-551, 2022.

DOI: 10.1080/10589759.2022.2071892

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130770902&doi=10.1080%2f10589759.2022.2071892&partnerID=40&md5=204f2e2122a047132545723032865c56

Segmentation of multiple features in Carbon Fiber Reinforced Polymers using a Convolutional Neural Network

P. Weinberger, B. Plank, B. Fröhler, J. Kastner and C. Heinzl, "Segmentation of multiple features in Carbon Fiber Reinforced Polymers using a Convolutional Neural Network" , 2022.

DOI: 10.1117/12.2612895

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132018706&doi=10.1117%2f12.2612895&partnerID=40&md5=14883c0e32a1f4b82ad4725ff5d9bd83

Sensitive vPSA-Exploring Sensitivity in Visual Parameter Space Analysis

B. Fröhler, T. Elberfeld, T. Möller, H. Hege, J. Maurer and C. Heinzl, "Sensitive vPSA-Exploring Sensitivity in Visual Parameter Space Analysis" , arXiv preprint arXiv:2204.01823 , 2022.

The long journey to the training of a deep neural network for segmenting pores and fibers

P. Weinberger, M. Yosifov, B. Fröhler, J. Kastner and C. Heinzl, "The long journey to the training of a deep neural network for segmenting pores and fibers" in iCT2022 , 2022. pp. 6.

Towards remote analytics in nondestructive testing

A. Gall, B. Fröhler, O. Strnad, C. Anthes and C. Heinzl, "Towards remote analytics in nondestructive testing" in AVI'22 Workshop Proceedings:``Enhancing Cross-reality Applicationsz and User Experiences'' , 2022.

Visual Coherence for Cross-Virtuality Analytics

F. Pointecker, M. Dalpiaz, P. Kainberger, A. Gall, B. Fröhler, C. Heinzl and C. Anthes, "Visual Coherence for Cross-Virtuality Analytics" in Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022 , 2022. pp. 161-166.

DOI: 10.1109/ISMAR-Adjunct57072.2022.00037

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146054711&doi=10.1109%2fISMAR-Adjunct57072.2022.00037&partnerID=40&md5=dc85e45ef2d091eb1ce500824bb0635f

Visualization Techniques for the Comparative Analysis of Multivariate Data of Fiber Reinforced Polymers

A. Heim, J. Maurer, J. Kastner and C. Heinzl, "Visualization Techniques for the Comparative Analysis of Multivariate Data of Fiber Reinforced Polymers" in iCT2022 , 2022. pp. 10.

Assessing the effect of sample orientation on dimensional X-ray computed tomography through experimental and simulated data

H. Villarraga-Gómez, A. Amirkhanov, C. Heinzl and S. Smith, "Assessing the effect of sample orientation on dimensional X-ray computed tomography through experimental and simulated data" , Measurement: Journal of the International Measurement Confederation , vol. 178, 2021.

DOI: 10.1016/j.measurement.2021.109343

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104326478&doi=10.1016%2fj.measurement.2021.109343&partnerID=40&md5=1afd457199b1a1bd92d9864477795729

IMNDT: Immersive workspace for the analysis of multidimensional material data from non-destructive testing

A. Gall, E. Gröller and C. Heinzl, "IMNDT: Immersive workspace for the analysis of multidimensional material data from non-destructive testing" , 2021.

DOI: 10.1145/3489849.3489851

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121470332&doi=10.1145%2f3489849.3489851&partnerID=40&md5=847070e2d387bde919164128def5accd

Analysis and comparison of algorithms for the tomographic reconstruction of curved fibres

B. Fröhler, T. Elberfeld, T. Möller, H. Hege, J. De Beenhouwer, J. Sijbers, J. Kastner and C. Heinzl, "Analysis and comparison of algorithms for the tomographic reconstruction of curved fibres" , Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 328-341, 2020.

DOI: 10.1080/10589759.2020.1774583

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087512093&doi=10.1080%2f10589759.2020.1774583&partnerID=40&md5=41cc1ebf545ff031ade088c7d68746ca

Cross-virtuality visualization, interaction and collaboration

A. Riegler, C. Heinzl, M. Brunner, B. Fröhler, C. Anthes, C. Holzmann, S. Auer, C. Leitner, H. Jetter, J. Herbert, J. Friedl, F. Pointecker, D. Schwajda and S. Tripathi, "Cross-virtuality visualization, interaction and collaboration" , 2020.

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098133861&partnerID=40&md5=baec8e17dc29251e17e53a3963813d1b

A visual tool for the analysis of algorithms for tomographic fiber reconstruction in materials science

B. Fröhler, T. Elberfeld, T. Möller, H. Hege, J. Weissenböck, J. De Beenhouwer, J. Sijbers, J. Kastner and C. Heinzl, "A visual tool for the analysis of algorithms for tomographic fiber reconstruction in materials science" , Computer Graphics Forum , vol. 38, no. 3, pp. 273-283, 2019.

DOI: 10.1111/cgf.13688

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070111292&doi=10.1111%2fcgf.13688&partnerID=40&md5=8e0b898976f55111911ca623173e3905

Dynamic Volume Lines: Visual Comparison of 3D Volumes through Space-filling Curves

J. Weissenböck, B. Fröhler, E. Gröller, J. Kastner and C. Heinzl, "Dynamic Volume Lines: Visual Comparison of 3D Volumes through Space-filling Curves" , IEEE Transactions on Visualization and Computer Graphics , vol. 25, no. 1, pp. 1040-1049, 2019.

DOI: 10.1109/TVCG.2018.2864510

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051785440&doi=10.1109%2fTVCG.2018.2864510&partnerID=40&md5=1d0baf8e6c655fe96fac4ebb1dcc41a0

Finite element modeling of nano porous sintered silver material using computed tomography images [Finite-Elemente-Modellierung von nano-porösem gesinterten Silber unter Verwendung von Computertomographiebildern]

B. Meyghani, M. Awang, P. Bokam, B. Plank, C. Heinzl and K. Siow, "Finite element modeling of nano porous sintered silver material using computed tomography images [Finite-Elemente-Modellierung von nano-porösem gesinterten Silber unter Verwendung von Computertomographiebildern]" , Materialwissenschaft und Werkstofftechnik , vol. 50, no. 5, pp. 533-538, 2019.

DOI: 10.1002/mawe.201800231

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065462764&doi=10.1002%2fmawe.201800231&partnerID=40&md5=d4d9518e505c920909b817429082b38f

Stress analysis of nano porous material using computed tomography images [Spannungsanalyse von nanoporösem Material mittels Computertomographie-Aufnahmen]

B. Meyghani, M. Awang, S. Emamian, B. Plank, H. Christoph and K. Siow, "Stress analysis of nano porous material using computed tomography images [Spannungsanalyse von nanoporösem Material mittels Computertomographie-Aufnahmen]" , Materialwissenschaft und Werkstofftechnik , vol. 50, no. 3, pp. 234-239, 2019.

DOI: 10.1002/mawe.201800206

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062682079&doi=10.1002%2fmawe.201800206&partnerID=40&md5=63233d088bd1dbf9e5cab843229fa01b

Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study

T. Elberfeld, J. De Beenhouwer, A. Dekker, C. Heinzl and J. Sijbers, "Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study" , Journal of Nondestructive Evaluation , vol. 37, no. 3, 2018.

DOI: 10.1007/s10921-018-0514-0

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050729929&doi=10.1007%2fs10921-018-0514-0&partnerID=40&md5=c7a679b34c695d1f6c4c555089d09cc9

Visual analysis of void and reinforcement characteristics in X-ray computed tomography dataset series of fiber-reinforced polymers

M. Schiwarth, J. Weissenböck, B. Plank, B. Fröhler, C. Heinzl and J. Kastner, "Visual analysis of void and reinforcement characteristics in X-ray computed tomography dataset series of fiber-reinforced polymers" , 2018.

DOI: 10.1088/1757-899X/406/1/012014

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054221856&doi=10.1088%2f1757-899X%2f406%2f1%2f012014&partnerID=40&md5=e1757458a87eb396d4743ad19f658d5a

Interactive Exploration and Visualization Using MetaTracts extracted from Carbon Fiber Reinforced Composites

A. Bhattacharya, J. Weissenböck, R. Wenger, A. Amirkhanov, J. Kastner and C. Heinzl, "Interactive Exploration and Visualization Using MetaTracts extracted from Carbon Fiber Reinforced Composites" , IEEE Transactions on Visualization and Computer Graphics , vol. 23, no. 8, pp. 1988-2002, 2017.

DOI: 10.1109/TVCG.2016.2582158

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028420369&doi=10.1109%2fTVCG.2016.2582158&partnerID=40&md5=945dd39859540703a4a5184e68ab2ced

PorosityAnalyzer: Visual analysis and evaluation of segmentation pipelines to determine the porosity in fiber-reinforced polymers

J. Weissenböck, A. Amirkhanov, E. Gröller, J. Kastner and C. Heinzl, "PorosityAnalyzer: Visual analysis and evaluation of segmentation pipelines to determine the porosity in fiber-reinforced polymers" , 2017. pp. 101-110.

DOI: 10.1109/VAST.2016.7883516

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017223068&doi=10.1109%2fVAST.2016.7883516&partnerID=40&md5=983faa6c728e1f460f25e9ca1e0dca22

Processing, analysis and visualization of CT data

C. Heinzl, A. Amirkhanov and J. Kastner, Processing, analysis and visualization of CT data. .... 2017.

DOI: 10.1007/978-3-319-59573-3_4

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042821877&doi=10.1007%2f978-3-319-59573-3_4&partnerID=40&md5=a3cd9f7f6fb2378cfb4e0eb7a4772fb9

STAR: Visual Computing in Materials Science

C. Heinzl and S. Stappen, "STAR: Visual Computing in Materials Science" , Computer Graphics Forum , vol. 36, no. 3, pp. 647-666, 2017.

DOI: 10.1111/cgf.13214

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85022211630&doi=10.1111%2fcgf.13214&partnerID=40&md5=759eccf10dae4f179d887d0976e1f48d

GEMSe: Visualization-Guided Exploration of Multi-channel Segmentation Algorithms

B. Fröhler, T. Möller and C. Heinzl, "GEMSe: Visualization-Guided Exploration of Multi-channel Segmentation Algorithms" , Computer Graphics Forum , vol. 35, no. 3, pp. 191-200, 2016.

DOI: 10.1111/cgf.12895

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979031827&doi=10.1111%2fcgf.12895&partnerID=40&md5=3f4e8e4fb7131abc74096c04ff29dba7

Quantitative evaluation of induced porosity reference samples implemented by drill hole in CFRP using XCT and various segmentation parameters

G. Rao, B. Plank, C. Heinzl and J. Kastner, "Quantitative evaluation of induced porosity reference samples implemented by drill hole in CFRP using XCT and various segmentation parameters" , 2016.

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018597185&partnerID=40&md5=e9db4eec0a2faf2c99dbf3bf4e656446

Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests

A. Amirkhanov, D. Salaberger, J. Kastner, M. Gröller and C. Heinzl, "Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests" , Computer Graphics Forum , vol. 35, no. 3, pp. 201-210, 2016.

DOI: 10.1111/cgf.12896

Datei: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979076007&doi=10.1111%2fcgf.12896&partnerID=40&md5=12612f4b5ffcc9fc51d9e6b4ebd3ea66