@inproceedings{CoconuUllmerPaaretal.2018, author = {Coconu, Liviu and Ullmer, Brygg and Paar, Philip and Liu, Jing and Konkel, Miriam and Hege, Hans-Christian}, title = {A smartphone-based tangible interaction approach for landscape visualization.}, series = {PerDis '18 Proceedings of the 7th ACM International Symposium on Pervasive Displays, Munich, Germany, June 6-8, 2018}, booktitle = {PerDis '18 Proceedings of the 7th ACM International Symposium on Pervasive Displays, Munich, Germany, June 6-8, 2018}, publisher = {ACM}, address = {New York, NY, USA}, doi = {10.1145/3205873.3210707}, pages = {no. 23}, year = {2018}, abstract = {The use of tangible interfaces for navigation of landscape scenery - for example, lost places re-created in 3D - has been pursued and articulated as a promising, impactful application of interactive visualization. In this demonstration, we present a modern, low-cost implementation of a previously-realized multimodal gallery installation. Our demonstration centers upon the versatile usage of a smartphone for sensing, navigating, and (optionally) displaying element on a physical surface in tandem with a larger, more immersive display.}, language = {en} } @misc{NavaYazdaniHegevonTycowiczetal., author = {Nava-Yazdani, Esfandiar and Hege, Hans-Christian and von Tycowicz, Christoph and Sullivan, T. J.}, title = {A Shape Trajectories Approach to Longitudinal Statistical Analysis}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-69759}, abstract = {For Kendall's shape space we determine analytically Jacobi fields and parallel transport, and compute geodesic regression. Using the derived expressions, we can fully leverage the geometry via Riemannian optimization and reduce the computational expense by several orders of magnitude. The methodology is demonstrated by performing a longitudinal statistical analysis of epidemiological shape data. As application example we have chosen 3D shapes of knee bones, reconstructed from image data of the Osteoarthritis Initiative. Comparing subject groups with incident and developing osteoarthritis versus normal controls, we find clear differences in the temporal development of femur shapes. This paves the way for early prediction of incident knee osteoarthritis, using geometry data only.}, language = {en} } @inproceedings{NadobnyWustStallingetal.1997, author = {Nadobny, Jacek and Wust, Peter and Stalling, Detlev and Hege, Hans-Christian and Deuflhard, Peter and Felix, Roland}, title = {A Quantitative Comparison Between VSIE and the FDTD Method Using Electrically Equivalent Patient and Antenna Models}, series = {Proceedings of 16th Annual Meeting of the European Society for Hyperthermic Oncology ESHO-97}, booktitle = {Proceedings of 16th Annual Meeting of the European Society for Hyperthermic Oncology ESHO-97}, address = {Berlin, Germany}, pages = {145}, year = {1997}, language = {en} } @inproceedings{BaumHege2006, author = {Baum, Daniel and Hege, Hans-Christian}, title = {A Point-matching based algorithm for 3D surface alignment of drug-sized molecules}, series = {Computational Life Sciences II, Second International Symposium, CompLife 2006, Cambridge (UK), Sept. 2006}, volume = {4216}, booktitle = {Computational Life Sciences II, Second International Symposium, CompLife 2006, Cambridge (UK), Sept. 2006}, publisher = {Springer}, doi = {10.1007/11875741_18}, pages = {183 -- 193}, year = {2006}, language = {en} } @inproceedings{HanikHegevonTycowicz, author = {Hanik, Martin and Hege, Hans-Christian and von Tycowicz, Christoph}, title = {A Nonlinear Hierarchical Model for Longitudinal Data on Manifolds}, series = {2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)}, booktitle = {2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)}, doi = {10.1109/ISBI52829.2022.9761465}, pages = {1 -- 5}, abstract = {Large longitudinal studies provide lots of valuable information, especially in medical applications. A problem which must be taken care of in order to utilize their full potential is that of correlation between intra-subject measurements taken at different times. For data in Euclidean space this can be done with hierarchical models, that is, models that consider intra-subject and between-subject variability in two different stages. Nevertheless, data from medical studies often takes values in nonlinear manifolds. Here, as a first step, geodesic hierarchical models have been developed that generalize the linear ansatz by assuming that time-induced intra-subject variations occur along a generalized straight line in the manifold. However, this is often not the case (e.g., periodic motion or processes with saturation). We propose a hierarchical model for manifold-valued data that extends this to include trends along higher-order curves, namely B{\´e}zier splines in the manifold. To this end, we present a principled way of comparing shape trends in terms of a functional-based Riemannian metric. Remarkably, this metric allows efficient, yet simple computations by virtue of a variational time discretization requiring only the solution of regression problems. We validate our model on longitudinal data from the osteoarthritis initiative, including classification of disease progression.}, language = {en} } @misc{NavaYazdaniHegevonTycowicz, author = {Nava-Yazdani, Esfandiar and Hege, Hans-Christian and von Tycowicz, Christoph}, title = {A Hierarchical Geodesic Model for Longitudinal Analysis on Manifolds}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85187}, abstract = {In many applications, geodesic hierarchical models are adequate for the study of temporal observations. We employ such a model derived for manifold-valued data to Kendall's shape space. In particular, instead of the Sasaki metric, we adapt a functional-based metric, which increases the computational efficiency and does not require the implementation of the curvature tensor. We propose the corresponding variational time discretization of geodesics and employ the approach for longitudinal analysis of 2D rat skulls shapes as well as 3D shapes derived from an imaging study on osteoarthritis. Particularly, we perform hypothesis test and estimate the mean trends.}, language = {en} } @article{NavaYazdaniHegevonTycowicz, author = {Nava-Yazdani, Esfandiar and Hege, Hans-Christian and von Tycowicz, Christoph}, title = {A Hierarchical Geodesic Model for Longitudinal Analysis on Manifolds}, series = {Journal of Mathematical Imaging and Vision}, volume = {64}, journal = {Journal of Mathematical Imaging and Vision}, number = {4}, doi = {10.1007/s10851-022-01079-x}, pages = {395 -- 407}, abstract = {In many applications, geodesic hierarchical models are adequate for the study of temporal observations. We employ such a model derived for manifold-valued data to Kendall's shape space. In particular, instead of the Sasaki metric, we adapt a functional-based metric, which increases the computational efficiency and does not require the implementation of the curvature tensor. We propose the corresponding variational time discretization of geodesics and employ the approach for longitudinal analysis of 2D rat skulls shapes as well as 3D shapes derived from an imaging study on osteoarthritis. Particularly, we perform hypothesis test and estimate the mean trends.}, language = {en} } @misc{SieberKuhnHegeetal., author = {Sieber, Moritz and Kuhn, Alexander and Hege, Hans-Christian and Paschereit, C. Oliver and Oberleithner, Kilian}, title = {A Graphical Representation of the Spectral Proper Orthogonal Decomposition}, series = {68th Annual Meeting of the APS Division of Fluid Dynamics, Gallery of Fluid Motion, Nov 22-24, 2015, Boston, MA, USA.}, journal = {68th Annual Meeting of the APS Division of Fluid Dynamics, Gallery of Fluid Motion, Nov 22-24, 2015, Boston, MA, USA.}, abstract = {We consider the spectral proper orthogonal decomposition (SPOD) for experimental data of a turbulent swirling jet. This newly introduced method combines the advantages of spectral methods, such as Fourier decomposition or dynamic mode decomposition, with the energy-ranked proper orthogonal decomposition (POD). This poster visualizes how the modal energy spectrum transitions from the spectral purity of Fourier space to the sparsity of POD space. The transition is achieved by changing a single parameter - the width of the SPOD filter. Each dot in the 3D space corresponds to an SPOD mode pair, where the size and color indicates its spectral coherence. What we notice is that neither the Fourier nor the POD spectrum achieves a clear separation of the dynamic phenomena. Scanning through the graph from the front plane (Fourier) to the back plane (POD), we observe how three highly coherent SPOD modes emerge from the dispersed Fourier spectrum and later branch out into numerous POD modes. The spatial properties of these three individual SPOD modes are displayed in the back of the graph using line integral convolution colored by vorticity. The first two modes correspond to single-helical global instabilities that are well known for these flows. Their coexistence, however, has not been observed until now. The third mode is of double- helical shape and has not been observed so far. For this considered data set and many others, the SPOD is superior in identification of coherent structures in turbulent flows. Hopefully, it gives access to new fluid dynamic phenomena and enriches the available methods.}, language = {en} } @misc{NavaYazdaniHegevonTycowicz, author = {Nava-Yazdani, Esfandiar and Hege, Hans-Christian and von Tycowicz, Christoph}, title = {A Geodesic Mixed Effects Model in Kendall's Shape Space}, series = {Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)}, journal = {Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-74621}, abstract = {In many applications, geodesic hierarchical models are adequate for the study of temporal observations. We employ such a model derived for manifold-valued data to Kendall's shape space. In particular, instead of the Sasaki metric, we adapt a functional-based metric, which increases the computational efficiency and does not require the implementation of the curvature tensor. We propose the corresponding variational time discretization of geodesics and apply the approach for the estimation of group trends and statistical testing of 3D shapes derived from an open access longitudinal imaging study on osteoarthritis.}, language = {en} } @inproceedings{NavaYazdaniHegevonTycowicz, author = {Nava-Yazdani, Esfandiar and Hege, Hans-Christian and von Tycowicz, Christoph}, title = {A Geodesic Mixed Effects Model in Kendall's Shape Space}, series = {Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)}, volume = {11846}, booktitle = {Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)}, doi = {10.1007/978-3-030-33226-6_22}, pages = {209 -- 218}, abstract = {In many applications, geodesic hierarchical models are adequate for the study of temporal observations. We employ such a model derived for manifold-valued data to Kendall's shape space. In particular, instead of the Sasaki metric, we adapt a functional-based metric, which increases the computational efficiency and does not require the implementation of the curvature tensor. We propose the corresponding variational time discretization of geodesics and apply the approach for the estimation of group trends and statistical testing of 3D shapes derived from an open access longitudinal imaging study on osteoarthritis.}, language = {en} }