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3. Exploration of Differentiability in a Proton Computed Tomography Simulation Framework

Author

Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Blühdorn, Johannes, Bodova, Tea, Borshchov, Vyacheslav, Brink, Anthony van den, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Kusch, Lisa, Leonhardt, Viktor, Mehendale, Shruti, Mulawade, Raju Ningappa, Odland, Odd Harald, O'Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Pochampalli, Rohit, Protsenko, Maksym, Rauch, Max, Rehman, Attiq Ur, Richter, Matthias, Röhrich, Dieter, Sagebaum, Max, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, RenZheng, Yang, Shiming, and Zillien, Sebastian

Subjects
Physics - Medical Physics, Computer Science - Mathematical Software
Abstract

Objective. Algorithmic differentiation (AD) can be a useful technique to numerically optimize design and algorithmic parameters by, and quantify uncertainties in, computer simulations. However, the effectiveness of AD depends on how "well-linearizable" the software is. In this study, we assess how promising derivative information of a typical proton computed tomography (pCT) scan computer simulation is for the aforementioned applications. Approach. This study is mainly based on numerical experiments, in which we repeatedly evaluate three representative computational steps with perturbed input values. We support our observations with a review of the algorithmic steps and arithmetic operations performed by the software, using debugging techniques. Main results. The model-based iterative reconstruction (MBIR) subprocedure (at the end of the software pipeline) and the Monte Carlo (MC) simulation (at the beginning) were piecewise differentiable. Jumps in the MBIR function arose from the discrete computation of the set of voxels intersected by a proton path. Jumps in the MC function likely arose from changes in the control flow that affect the amount of consumed random numbers. The tracking algorithm solves an inherently non-differentiable problem. Significance. The MC and MBIR codes are ready for the integration of AD, and further research on surrogate models for the tracking subprocedure is necessary., Comment: 27 pages, 11 figures

Published
2022

4. A survey on applications of augmented, mixed and virtual reality for nature and environment

Author

Rambach, Jason, Lilligreen, Gergana, Schäfer, Alexander, Bankanal, Ramya, Wiebel, Alexander, and Stricker, Didier

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computers and Society, Computer Science - Computer Science and Game Theory
Abstract

Augmented reality (AR), virtual reality (VR) and mixed reality (MR) are technologies of great potential due to the engaging and enriching experiences they are capable of providing. Their use is rapidly increasing in diverse fields such as medicine, manufacturing or entertainment. However, the possibilities that AR, VR and MR offer in the area of environmental applications are not yet widely explored. In this paper we present the outcome of a survey meant to discover and classify existing AR/VR/MR applications that can benefit the environment or increase awareness on environmental issues. We performed an exhaustive search over several online publication access platforms and past proceedings of major conferences in the fields of AR/VR/MR. Identified relevant papers were filtered based on novelty, technical soundness, impact and topic relevance, and classified into different categories. Referring to the selected papers, we discuss how the applications of each category are contributing to environmental protection, preservation and sensitization purposes. We further analyse these approaches as well as possible future directions in the scope of existing and upcoming AR/VR/MR enabling technologies.

Published
2020

6. A Survey on Applications of Augmented, Mixed and Virtual Reality for Nature and Environment

Author

Rambach, Jason, Lilligreen, Gergana, Schäfer, Alexander, Bankanal, Ramya, Wiebel, Alexander, Stricker, Didier, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Jessie Y. C., editor, and Fragomeni, Gino, editor

Published
2021
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7. Rendering Tree Roots Outdoors: A Comparison Between Optical See Through Glasses and Smartphone Modules for Underground Augmented Reality Visualization

Author

Lilligreen, Gergana, Marsenger, Philipp, Wiebel, Alexander, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Jessie Y. C., editor, and Fragomeni, Gino, editor

Published
2021
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12. Exploration of differentiability in a proton computed tomography simulation framework

Author

Aehle, Max, primary, Alme, Johan, additional, Gábor Barnaföldi, Gergely, additional, Blühdorn, Johannes, additional, Bodova, Tea, additional, Borshchov, Vyacheslav, additional, van den Brink, Anthony, additional, Eikeland, Viljar, additional, Feofilov, Gregory, additional, Garth, Christoph, additional, Gauger, Nicolas R, additional, Grøttvik, Ola, additional, Helstrup, Håvard, additional, Igolkin, Sergey, additional, Keidel, Ralf, additional, Kobdaj, Chinorat, additional, Kortus, Tobias, additional, Kusch, Lisa, additional, Leonhardt, Viktor, additional, Mehendale, Shruti, additional, Ningappa Mulawade, Raju, additional, Harald Odland, Odd, additional, O’Neill, George, additional, Papp, Gábor, additional, Peitzmann, Thomas, additional, Pettersen, Helge Egil Seime, additional, Piersimoni, Pierluigi, additional, Pochampalli, Rohit, additional, Protsenko, Maksym, additional, Rauch, Max, additional, Ur Rehman, Attiq, additional, Richter, Matthias, additional, Röhrich, Dieter, additional, Sagebaum, Max, additional, Santana, Joshua, additional, Schilling, Alexander, additional, Seco, Joao, additional, Songmoolnak, Arnon, additional, Sudár, Ákos, additional, Tambave, Ganesh, additional, Tymchuk, Ihor, additional, Ullaland, Kjetil, additional, Varga-Kofarago, Monika, additional, Volz, Lennart, additional, Wagner, Boris, additional, Wendzel, Steffen, additional, Wiebel, Alexander, additional, Xiao, RenZheng, additional, Yang, Shiming, additional, and Zillien, Sebastian, additional

Published
2023
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13. Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter

Author

Schilling, Alexander, primary, Aehle, Max, additional, Alme, Johan, additional, Barnaföldi, Gergely Gábor, additional, Bodova, Tea, additional, Borshchov, Vyacheslav, additional, van den Brink, Anthony, additional, Eikeland, Viljar, additional, Feofilov, Gregory, additional, Garth, Christoph, additional, Gauger, Nicolas R, additional, Grøttvik, Ola, additional, Helstrup, Håvard, additional, Igolkin, Sergey, additional, Keidel, Ralf, additional, Kobdaj, Chinorat, additional, Kortus, Tobias, additional, Leonhardt, Viktor, additional, Mehendale, Shruti, additional, Ningappa Mulawade, Raju, additional, Harald Odland, Odd, additional, O’Neill, George, additional, Papp, Gábor, additional, Peitzmann, Thomas, additional, Pettersen, Helge Egil Seime, additional, Piersimoni, Pierluigi, additional, Protsenko, Maksym, additional, Rauch, Max, additional, Ur Rehman, Attiq, additional, Richter, Matthias, additional, Röhrich, Dieter, additional, Santana, Joshua, additional, Seco, Joao, additional, Songmoolnak, Arnon, additional, Sudár, Ákos, additional, Tambave, Ganesh, additional, Tymchuk, Ihor, additional, Ullaland, Kjetil, additional, Varga-Kofarago, Monika, additional, Volz, Lennart, additional, Wagner, Boris, additional, Wendzel, Steffen, additional, Wiebel, Alexander, additional, Xiao, RenZheng, additional, Yang, Shiming, additional, and Zillien, Sebastian, additional

Published
2023
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15. On the Lamb Vector and the Hydrodynamic Charge

Author

Rousseaux, Germain, Seifer, Shahar, Steinberg, Victor, and Wiebel, Alexander

Subjects
Physics - Classical Physics
Abstract

This work is an attempt to test the concept of hydrodynamic charge (analogous to the electric charge in Electromagnetism) in the simple case of a coherent structure such as the Burgers vortex. We provide experimental measurements of both the so-called Lamb vector and its divergence (the charge) by two-dimensional Particle Image Velocimetry. In addition, we perform a Helmholtz-Hodge decomposition of the Lamb vector in order to explore its topological features. We compare the charge with the well-known Q criterion in order to assess its interest in detecting and characterizing coherent structure. Usefulness of this concept in studies of vortex dynamics is demonstrated., Comment: 16 pages

Published
2005
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17. Lagrangian Visualization of Flow-Embedded Surface Structures

Author

Garth, Christoph, Wiebel, Alexander, Tricoche, Xavier, Joy, Ken, and Scheuermann, Gerik

Subjects
flow visualization, separation/attachment, Lagrangian analysis
Abstract

The notions of Finite-Time Lyapunov Exponent (FTLE) and Lagrangian Coherent Structures provide a strong framework for the analysis and visualization of complex technical flows. Their definition is simple and intuitive, and they are built on a deep theoretical foundation. We apply these concepts to enable the analysis of flows in the immediate vicinity of the boundaries of flow-embedded objects by limiting the Lagrangian analysis to surfaces closely neighboring these boundaries. To this purpose, we present an approach to approximate FTLE fields over such surfaces. Furthermore, we achieve an effective depiction of boundary-related flow structures such as separation and attachment over object boundaries and specific insight into the surrounding flow using several specifically chosen visualization techniques. We document the applicability of our methods by presenting a number of application examples.

Published
2008

18. Computation of Localized Flow for Steady and Unsteady Vector Fields and Its Applications

Author

Wiebel, Alexander, Garth, Christoph, and Scheuermann, Gerik

Abstract

In this paper we present an approach to the analysis of the contribution of a small subregion in a dataset to the global flow. To this purpose, we subtract the potential flow that is induced by the boundary of the sub-domain from the original flow. Since the potential flow is free of both divergence and rotation, the localized flow field retains the original features. In contrast to similar approaches, by making explicit use of the boundary flow of the subregion, we manage to isolate the region-specific flow that contains exactly the local contribution of the considered subdomain to the global flow. In the remainder of the paper, we describe an implementation on unstructured grids in both two and three dimensions. We discuss the application of several widely used feature extraction methods on the localized flow, with an emphasis on topological schemes.

Published
2007

21. Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter

Author

Sub GRASP, Gravitational and Subatomic Physics (GRASP), Schilling, Alexander, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Santana, Joshua, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Zillien, Sebastian, Sub GRASP, Gravitational and Subatomic Physics (GRASP), Schilling, Alexander, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Santana, Joshua, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, and Zillien, Sebastian

Published
2023

22. Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter

Author

Schilling, Alexander, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Santana, Joshua, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Zillien, Sebastian, Schilling, Alexander, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Santana, Joshua, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, and Zillien, Sebastian

Abstract

Objective. Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots. Approach. We employ uncertainty-aware deep neural networks to predict the Bragg peak depth in an anthropomorphic phantom based on secondary charged particle detection in a silicon pixel telescope designed for proton computed tomography. The subsequently predicted Bragg peak positions, along with their uncertainties, are compared to the treatment plan, rejecting spots which are predicted to be outside the 95% confidence interval. The such-produced spot rejection rate presents a metric for the quality of the treatment fraction. Main results. The introduced spot rejection rate metric is shown to be well-defined for range predictors with well-calibrated uncertainties. Using this method, treatment errors in the form of lateral shifts can be detected down to 1 mm after around 1400 treated spots with spot intensities of 1 × 107 protons. The range verification model used in this metric predicts the Bragg peak depth to a mean absolute error of 1.107 ± 0.015 mm. Significance. Uncertainty-aware machine learning has potential applications in proton therapy quality control. This work presents the foundation for future developments in this area.

Published
2023

23. Exploration of differentiability in a proton computed tomography simulation framework

Author

Aehle, Max, Alme, Johan, Gábor Barnaföldi, Gergely, Blühdorn, Johannes, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Kusch, Lisa, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Pochampalli, Rohit, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Sagebaum, Max, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Zillien, Sebastian, Aehle, Max, Alme, Johan, Gábor Barnaföldi, Gergely, Blühdorn, Johannes, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Kusch, Lisa, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Pochampalli, Rohit, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Sagebaum, Max, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, and Zillien, Sebastian

Abstract

Objective. Gradient-based optimization using algorithmic derivatives can be a useful technique to improve engineering designs with respect to a computer-implemented objective function. Likewise, uncertainty quantification through computer simulations can be carried out by means of derivatives of the computer simulation. However, the effectiveness of these techniques depends on how ‘well-linearizable’ the software is. In this study, we assess how promising derivative information of a typical proton computed tomography (pCT) scan computer simulation is for the aforementioned applications. Approach. This study is mainly based on numerical experiments, in which we repeatedly evaluate three representative computational steps with perturbed input values. We support our observations with a review of the algorithmic steps and arithmetic operations performed by the software, using debugging techniques. Main results. The model-based iterative reconstruction (MBIR) subprocedure (at the end of the software pipeline) and the Monte Carlo (MC) simulation (at the beginning) were piecewise differentiable. However, the observed high density and magnitude of jumps was likely to preclude most meaningful uses of the derivatives. Jumps in the MBIR function arose from the discrete computation of the set of voxels intersected by a proton path, and could be reduced in magnitude by a ‘fuzzy voxels’ approach. The investigated jumps in the MC function arose from local changes in the control flow that affected the amount of consumed random numbers. The tracking algorithm solves an inherently non-differentiable problem. Significance. Besides the technical challenges of merely applying AD to existing software projects, the MC and MBIR codes must be adapted to compute smoother functions. For the MBIR code, we presented one possible approach for this while for the MC code, this will be subject to further research. For the tracking subprocedure, further research on surrogate models is necessary.

Published
2023

24. Exploration of differentiability in a proton computed tomography simulation framework

Author

Sub GRASP, Gravitational and Subatomic Physics (GRASP), Aehle, Max, Alme, Johan, Gábor Barnaföldi, Gergely, Blühdorn, Johannes, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Kusch, Lisa, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Pochampalli, Rohit, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Sagebaum, Max, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Zillien, Sebastian, Sub GRASP, Gravitational and Subatomic Physics (GRASP), Aehle, Max, Alme, Johan, Gábor Barnaföldi, Gergely, Blühdorn, Johannes, Bodova, Tea, Borshchov, Vyacheslav, van den Brink, Anthony, Eikeland, Viljar, Feofilov, Gregory, Garth, Christoph, Gauger, Nicolas R., Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Kusch, Lisa, Leonhardt, Viktor, Mehendale, Shruti, Ningappa Mulawade, Raju, Harald Odland, Odd, O’Neill, George, Papp, Gábor, Peitzmann, Thomas, Pettersen, Helge Egil Seime, Piersimoni, Pierluigi, Pochampalli, Rohit, Protsenko, Maksym, Rauch, Max, Ur Rehman, Attiq, Richter, Matthias, Röhrich, Dieter, Sagebaum, Max, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sudár, Ákos, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, and Zillien, Sebastian

Published
2023

25. A System for Combined Visualization of EEG and Diffusion Tensor Imaging Tractography Data

Author

Wiebel, Alexander, Müller, Cornelius, Garth, Christoph, Knösche, Thomas R., Farin, Gerald, Series editor, Hege, Hans-Christian, Series editor, Hoffman, David, Series editor, Johnson, Christopher R., Series editor, Polthier, Konrad, Series editor, Rumpf, Martin, Series editor, Westin, Carl-Fredrik, editor, Vilanova, Anna, editor, and Burgeth, Bernhard, editor

Published
2014
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26. Top Challenges in the Visualization of Engineering Tensor Fields

Author

Hlawitschka, Mario, Hotz, Ingrid, Kratz, Andrea, Marai, G. Elisabeta, Moreno, Rodrigo, Scheuermann, Gerik, Stommel, Markus, Wiebel, Alexander, Zhang, Eugene, Farin, Gerald, Series editor, Hege, Hans-Christian, Series editor, Hoffman, David, Series editor, Johnson, Christopher R., Series editor, Polthier, Konrad, Series editor, Rumpf, Martin, Series editor, Westin, Carl-Fredrik, editor, Vilanova, Anna, editor, and Burgeth, Bernhard, editor

Published
2014
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27. Definition, Extraction, and Validation of Pore Structures in Porous Materials

Author

Homberg, Ulrike, Baum, Daniel, Wiebel, Alexander, Prohaska, Steffen, Hege, Hans-Christian, Farin, Gerald, Series editor, Hege, Hans-Christian, Series editor, Hoffman, David, Series editor, Johnson, Christopher R., Series editor, Polthier, Konrad, Series editor, Rumpf, Martin, Series editor, Bremer, Peer-Timo, editor, Hotz, Ingrid, editor, Pascucci, Valerio, editor, and Peikert, Ronald, editor

Published
2014
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28. Visual Cue Based Corrective Feedback for Motor Skill Training in Mixed Reality: A Survey

Author

Diller, Florian, Scheuermann, Gerik, and Wiebel, Alexander

Abstract

When learning a motor skill it is helpful to get corrective feedback from an instructor. This will support the learner to execute the movement correctly. With modern technology, it is possible to provide this feedback via mixed reality. In most cases, this involves visual cues to help the user understand the corrective feedback. We analyzed recent research approaches utilizing visual cues for feedback in mixed reality. The scope of this article is visual feedback for motor skill learning, which involves physical therapy, exercise, rehabilitation etc. While some of the surveyed literature discusses therapeutic effects of the training, this article focuses on visualization techniques. We categorized the literature from a visualization standpoint, including visual cues, technology and characteristics of the feedback. This provided insights into how visual feedback in mixed reality is applied in the literature and how different aspects of the feedback are related. The insights obtained can help to better adjust future feedback systems to the target group and their needs. This article also provides a deeper understanding of the characteristics of the visual cues in general and promotes future, more detailed research on this topic.

Published
2024
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34. Topology Based Flow Analysis and Superposition Effects

Author

Ebling, Julia, Wiebel, Alexander, Garth, Christoph, Scheuermann, Gerik, Farin, Gerald, editor, Hege, Hans-Christian, editor, Hoffman, David, editor, Johnson, Christopher R., editor, Polthier, Konrad, editor, Rumpf, Martin, editor, Hauser, Helwig, editor, Hagen, Hans, editor, and Theisel, Holger, editor

Published
2007
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35. Saliency Clouds: Visual Analysis of Point Cloud-oriented Deep Neural Networks in DeepRL for Particle Physics

Author

Mulawade, Raju Ningappa, Garth, Christoph, and Wiebel, Alexander

Subjects
+Visualization+techniques%22">CCS Concepts: Human-centered computing --> Visualization techniques, +Neural+networks%22">Computing methodologies --> Neural networks, Human centered computing, Visualization techniques, Computing methodologies, Neural networks
Abstract

We develop and describe saliency clouds, that is, visualization methods employing explainable AI methods to analyze and interpret deep reinforcement learning (DeepRL) agents working on point cloud-based data. The agent in our application case is tasked to track particles in high energy physics and is still under development. The point clouds contain properties of particle hits on layers of a detector as the input to reconstruct the trajectories of the particles. Through visualization of the influence of different points, their possible connections in an implicit graph, and other features on the decisions of the policy network of the DeepRL agent, we aim to explain the decision making of the agent in tracking particles and thus support its development. In particular, we adapt gradient-based saliency mapping methods to work on these point clouds. We show how the properties of the methods, which were developed for image data, translate to the structurally different point cloud data. Finally, we present visual representations of saliency clouds supporting visual analysis and interpretation of the RL agent's policy network., Papers, Raju Ningappa Mulawade, Christoph Garth, and Alexander Wiebel

Published
2022
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36. Semi-Automatic Particle Tracking for and Visualization of Particle Detector Data

Author

Eschbach, Robin, Messerschmidt , Kai, Keidel, Ralf, and Wiebel, Alexander

Abstract

In high energy physics, tracking particles in point-based particle detector data is important to reconstruct the particles' trajectories. As the numbers of particles can be in the hundreds or over a thousand, automatic algorithmic tracking is usually preferred over manual tracking. However, in some cases, manual tracking is needed as a baseline to assess the quality of the algorithmic tracking. Tracking particle locations manually is time-consuming and challenging when dealing with thousands of particles in the same data frame. In this paper, we describe Semi-Automatic Particle Tracking (SAPT), a collection of methods that aid manual particle tracking and visualization. These methods aim to make related particle hits easier to recognize by stretching the data and hiding likely irrelevant hits based on an angle criterion. They also help with finding the most likely track among a set of intuitively selected detector hits. These methods, together with a prediction of the most probable continuation of a track that can simply be accepted by the human user, accelerate the manual tracking process tremendously. We demonstrate the usefulness and efficiency of our methods by applying them to simulation data of a detector for proton computed tomography (pCT)., Session IV, Robin Eschbach, Kai Messerschmidt, Ralf Keidel, and Alexander Wiebel

Published
2022
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39. Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks

Author

Pettersen, Helge Egil Seime, primary, Aehle, Max, additional, Alme, Johan, additional, Barnaföldi, Gergely Gábor, additional, Borshchov, Vyacheslav, additional, van den Brink, Anthony, additional, Chaar, Mamdouh, additional, Eikeland, Viljar, additional, Feofilov, Grigory, additional, Garth, Christoph, additional, Gauger, Nicolas R., additional, Genov, Georgi, additional, Grøttvik, Ola, additional, Helstrup, Håvard, additional, Igolkin, Sergey, additional, Keidel, Ralf, additional, Kobdaj, Chinorat, additional, Kortus, Tobias, additional, Leonhardt, Viktor, additional, Mehendale, Shruti, additional, Mulawade, Raju Ningappa, additional, Odland, Odd Harald, additional, Papp, Gábor, additional, Peitzmann, Thomas, additional, Piersimoni, Pierluigi, additional, Protsenko, Maksym, additional, Rehman, Attiq Ur, additional, Richter, Matthias, additional, Santana, Joshua, additional, Schilling, Alexander, additional, Seco, Joao, additional, Songmoolnak, Arnon, additional, Sølie, Jarle Rambo, additional, Tambave, Ganesh, additional, Tymchuk, Ihor, additional, Ullaland, Kjetil, additional, Varga-Kofarago, Monika, additional, Volz, Lennart, additional, Wagner, Boris, additional, Wendzel, Steffen, additional, Wiebel, Alexander, additional, Xiao, RenZheng, additional, Yang, Shiming, additional, Yokoyama, Hiroki, additional, Zillien, Sebastian, additional, and Röhrich, Dieter, additional

Published
2021
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40. Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks

Author

Pettersen, Helge Egil Seime, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Borshchov, Vyacheslav, van den Brink, Anthony, Chaar, Mamdouh, Eikeland, Viljar, Feofilov, Grigory, Garth, Christoph, Gauger, Nicolas R., Genov, Georgi, Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Mulawade, Raju Ningappa, Odland, Odd Harald, Papp, Gábor, Peitzmann, Thomas, Piersimoni, Pierluigi, Protsenko, Maksym, Rehman, Attiq Ur, Richter, Matthias, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sølie, Jarle Rambo, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Yokoyama, Hiroki, Zillien, Sebastian, Röhrich, Dieter, Pettersen, Helge Egil Seime, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Borshchov, Vyacheslav, van den Brink, Anthony, Chaar, Mamdouh, Eikeland, Viljar, Feofilov, Grigory, Garth, Christoph, Gauger, Nicolas R., Genov, Georgi, Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Mulawade, Raju Ningappa, Odland, Odd Harald, Papp, Gábor, Peitzmann, Thomas, Piersimoni, Pierluigi, Protsenko, Maksym, Rehman, Attiq Ur, Richter, Matthias, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sølie, Jarle Rambo, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Yokoyama, Hiroki, Zillien, Sebastian, and Röhrich, Dieter

Abstract

Background: Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and in situ treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality. We have investigated whether a convolutional neural network (CNN)-based filter is able to improve the image quality. Material and methods: The CNN was trained by simulation and reconstruction of tens of millions of proton and helium tracks. The CNN filter was then compared to simple energy loss threshold methods using the Area Under the Receiver Operating Characteristics curve (AUROC), and by comparing the image quality and Water Equivalent Path Length (WEPL) error of proton and helium radiographs filtered with the same methods. Results: The CNN method led to a considerable improvement of the AUROC, from 74.3% to 97.5% with protons and from 94.2% to 99.5% with helium. The CNN filtering reduced the WEPL error in the helium radiograph from 1.03 mm to 0.93 mm while no improvement was seen in the CNN filtered pRads.Conclusion: The CNN improved the filtering of proton and helium tracks. Only in the helium radiograph did this lead to improved image quality.

Published
2021

41. Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks

Author

Sub Subatomic Physics (SAP), Subatomic Physics, Pettersen, Helge Egil Seime, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Borshchov, Vyacheslav, van den Brink, Anthony, Chaar, Mamdouh, Eikeland, Viljar, Feofilov, Grigory, Garth, Christoph, Gauger, Nicolas R., Genov, Georgi, Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Mulawade, Raju Ningappa, Odland, Odd Harald, Papp, Gábor, Peitzmann, Thomas, Piersimoni, Pierluigi, Protsenko, Maksym, Rehman, Attiq Ur, Richter, Matthias, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sølie, Jarle Rambo, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Yokoyama, Hiroki, Zillien, Sebastian, Röhrich, Dieter, Sub Subatomic Physics (SAP), Subatomic Physics, Pettersen, Helge Egil Seime, Aehle, Max, Alme, Johan, Barnaföldi, Gergely Gábor, Borshchov, Vyacheslav, van den Brink, Anthony, Chaar, Mamdouh, Eikeland, Viljar, Feofilov, Grigory, Garth, Christoph, Gauger, Nicolas R., Genov, Georgi, Grøttvik, Ola, Helstrup, Håvard, Igolkin, Sergey, Keidel, Ralf, Kobdaj, Chinorat, Kortus, Tobias, Leonhardt, Viktor, Mehendale, Shruti, Mulawade, Raju Ningappa, Odland, Odd Harald, Papp, Gábor, Peitzmann, Thomas, Piersimoni, Pierluigi, Protsenko, Maksym, Rehman, Attiq Ur, Richter, Matthias, Santana, Joshua, Schilling, Alexander, Seco, Joao, Songmoolnak, Arnon, Sølie, Jarle Rambo, Tambave, Ganesh, Tymchuk, Ihor, Ullaland, Kjetil, Varga-Kofarago, Monika, Volz, Lennart, Wagner, Boris, Wendzel, Steffen, Wiebel, Alexander, Xiao, Ren Zheng, Yang, Shiming, Yokoyama, Hiroki, Zillien, Sebastian, and Röhrich, Dieter

Published
2021

47. Localized Flow and Analysis of 2D and 3D Vector Fields

Author

Wiebel, Alexander, Garth, Christoph, and Scheuermann, Gerik

Subjects
Physics::Fluid Dynamics, ddc:621.3, Physics, Engineering, Simulation, Modeling, Simulation Output Anlaysis, 3D vector fields, Visualization, CFD flows
Abstract

In this paper we present an approach to the analysis of the contribution of a small subregion in a dataset to the global flow. To this purpose, we subtract the potential flow that is induced by the boundary of the sub-domain from the original flow. Since the potential flow is free of both divergence and rotation, the localized flow field retains the original features. In contrast to similar approaches, by making explicit use of the boundary flow of the subregion, we manage to isolate the region-specific flow that contains exactly the local contribution of the considered subdomain to the global flow. In the remainder of the paper, we describe an implementation on unstructured grids in both two and three dimensions. We discuss the application of several widely used feature extraction methods on the localized flow, with an emphasis on topological schemes.

Published
2018

48. A Model of Spatial Directness in Interaction for Visualization

Author

Bruckner , Stefan, Isenberg , Tobias, Ropinski , Timo, Wiebel , Alexander, Analysis and Visualization ( AVIZ ), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Ulm University, and Fachhochschule Worms

Subjects
[ SCCO.COMP ] Cognitive science/Computer science
Abstract

To appear; International audience

Published
2018

50. A Model of Spatial Directness in Interactive Visualization

Author

Bruckner, Stefan, Isenberg, Tobias, Ropinski, Timo, Wiebel, Alexander, Bruckner, Stefan, Isenberg, Tobias, Ropinski, Timo, and Wiebel, Alexander

Abstract

We discuss the concept of directness in the context of spatial interaction with visualization. In particular, we propose a model that allows practitioners to analyze and describe the spatial directness of interaction techniques, ultimately to be able to better understand interaction issues that may affect usability. To reach these goals, we distinguish between different types of directness. Each type of directness depends on a particular mapping between different spaces, for which we consider the data space, the visualization space, the output space, the user space, the manipulation space, and the interaction space. In addition to the introduction of the model itself, we also show how to apply it to several real-world interaction scenarios in visualization, and thus discuss the resulting types of spatial directness, without recommending either more direct or more indirect interaction techniques. In particular, we will demonstrate descriptive and evaluative usage of the proposed model, and also briefly discuss its generative usage.

Published
2018
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