@inproceedings{BeckHegeSeebassetal.1996, author = {Beck, Rudolf and Hege, Hans-Christian and Seebaß, Martin and Wust, Peter and Deuflhard, Peter and Felix, Roland}, title = {Adaptive Finite Element Codes for Numerical Calculations in Hyperthermia Treatment Planning}, series = {Proceedings of the 17th Congress on Hyperthermic Oncology}, volume = {2}, booktitle = {Proceedings of the 17th Congress on Hyperthermic Oncology}, address = {Rome, Italy}, pages = {515 -- 517}, year = {1996}, language = {en} } @article{KastenReininghausHotzetal.2016, author = {Kasten, Jens and Reininghaus, Jan and Hotz, Ingrid and Hege, Hans-Christian and Noack, Bernd and Daviller, Guillaume and Morzyński, Marek}, title = {Acceleration feature points of unsteady shear flows}, series = {Archives of Mechanics}, volume = {68}, journal = {Archives of Mechanics}, number = {1}, pages = {55 -- 80}, year = {2016}, abstract = {A framework is proposed for extracting features in 2D transient flows, based on the acceleration field to ensure Galilean invariance. The minima of the acceleration magnitude, i.e. a superset of the acceleration zeros, are extracted and discriminated into vortices and saddle points --- based on the spectral properties of the velocity Jacobian. The extraction of topological features is performed with purely combinatorial algorithms from discrete computational topology. The feature points are prioritized with persistence, as a physically meaningful importance measure. These features are tracked in time with a robust algorithm for tracking features. Thus a space-time hierarchy of the minima is built and vortex merging events are detected. The acceleration feature extraction strategy is applied to three two-dimensional shear flows: (1) an incompressible periodic cylinder wake, (2) an incompressible planar mixing layer and (3) a weakly compressible planar jet. The vortex-like acceleration feature points are shown to be well aligned with acceleration zeros, maxima of the vorticity magnitude, minima of pressure field and minima of λ2.}, language = {en} } @article{LindowBaumProhaskaetal.2010, author = {Lindow, Norbert and Baum, Daniel and Prohaska, Steffen and Hege, Hans-Christian}, title = {Accelerated Visualization of Dynamic Molecular Surfaces}, series = {Comput. Graph. Forum}, volume = {29}, journal = {Comput. Graph. Forum}, doi = {10.1111/j.1467-8659.2009.01693.x}, pages = {943 -- 952}, year = {2010}, language = {en} } @article{FroehlerElberfeldMoelleretal., author = {Fr{\"o}hler, Bernhard and Elberfeld, Tim and M{\"o}ller, Torsten and Hege, Hans-Christian and Weissenb{\"o}ck, Johannes and De Beenhouwer, Jan and Sijbers, Jan and Kastner, Johann and Heinzl, Christoph}, title = {A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science}, series = {Computer Graphics Forum}, volume = {38}, journal = {Computer Graphics Forum}, number = {3}, doi = {10.1111/cgf.13688}, pages = {273 -- 283}, abstract = {We present visual analysis methods for the evaluation of tomographic fiber reconstruction algorithms by means of analysis, visual debugging and comparison of reconstructed fibers in materials science. The methods are integrated in a tool (FIAKER) that supports the entire workflow. It enables the analysis of various fiber reconstruction algorithms, of differently parameterized fiber reconstruction algorithms and of individual steps in iterative fiber reconstruction algorithms. Insight into the performance of fiber reconstruction algorithms is obtained by a list-based ranking interface. A 3D view offers interactive visualization techniques to gain deeper insight, e.g., into the aggregated quality of the examined fiber reconstruction algorithms and parameterizations. The tool was designed in close collaboration with researchers who work with fiber-reinforced polymers on a daily basis and develop algorithms for tomographic reconstruction and characterization of such materials. We evaluate the tool using synthetic datasets as well as tomograms of real materials. Five case studies certify the usefulness of the tool, showing that it significantly accelerates the analysis and provides valuable insights that make it possible to improve the fiber reconstruction algorithms. The main contribution of the paper is the well-considered combination of methods and their seamless integration into a visual tool that supports the entire workflow. Further findings result from the analysis of (dis-)similarity measures for fibers as well as from the discussion of design decisions. It is also shown that the generality of the analytical methods allows a wider range of applications, such as the application in pore space analysis.}, language = {en} } @article{VohraHarthIsoeetal., author = {Vohra, Sumit Kumar and Harth, Philipp and Isoe, Yasuko and Bahl, Armin and Fotowat, Haleh and Engert, Florian and Hege, Hans-Christian and Baum, Daniel}, title = {A Visual Interface for Exploring Hypotheses about Neural Circuits}, series = {IEEE Transactions on Visualization and Computer Graphics}, journal = {IEEE Transactions on Visualization and Computer Graphics}, doi = {10.1109/TVCG.2023.3243668}, abstract = {One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned task by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa.}, language = {en} } @article{SipsKothurUngeretal.2012, author = {Sips, Mike and Kothur, Patrick and Unger, Andrea and Hege, Hans-Christian and Dransch, Doris}, title = {A Visual Analytics Approach to Multiscale Exploration of Environmental Time Series}, series = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18}, journal = {IEEE Transactions on Visualization and Computer Graphics}, number = {12}, doi = {10.1109/TVCG.2012.191}, pages = {2899 -- 2907}, year = {2012}, abstract = {We present a Visual Analytics approach that addresses the detection of interesting patterns in numerical time series, specifically from environmental sciences. Crucial for the detection of interesting temporal patterns are the time scale and the starting points one is looking at. Our approach makes no assumption about time scale and starting position of temporal patterns and consists of three main steps: an algorithm to compute statistical values for all possible time scales and starting positions of intervals, visual identification of potentially interesting patterns in a matrix visualization, and interactive exploration of detected patterns. We demonstrate the utility of this approach in two scientific scenarios and explain how it allowed scientists to gain new insight into the dynamics of environmental systems.}, language = {en} } @inproceedings{ProhaskaHegeGiehletal.2003, author = {Prohaska, Steffen and Hege, Hans-Christian and Giehl, Michael and Gowin, Wolfgang}, title = {A Virtual Laboratory for Assessment of Bone Biopsies}, series = {14th IAA Humans in Space Symposium}, booktitle = {14th IAA Humans in Space Symposium}, address = {Banff, Alberta, Canada}, pages = {7}, year = {2003}, language = {en} } @inproceedings{WeinkaufSahnerTheiseletal.2007, author = {Weinkauf, Tino and Sahner, Jan and Theisel, Holger and Hege, Hans-Christian and Seidel, Hans-Peter}, title = {A unified feature extraction architecture}, series = {Active Flow Control}, booktitle = {Active Flow Control}, publisher = {Springer Berlin/Heidelberg}, doi = {10.1007/978-3-540-71439-2_8}, pages = {119 -- 133}, year = {2007}, language = {en} } @article{BrandtRohlfingRybaketal.2005, author = {Brandt, Robert and Rohlfing, Torsten and Rybak, J{\"u}rgen and Krofczik, Sabine and Maye, Alexander and Westerhoff, Malte and Hege, Hans-Christian and Menzel, Randolf}, title = {A three-dimensional average-shape atlas of the honeybee brain and its applications}, series = {Journal of Comparative Neurology}, volume = {492(1)}, journal = {Journal of Comparative Neurology}, pages = {1 -- 19}, year = {2005}, language = {en} } @article{UdvaryHarthMackeetal., author = {Udvary, Daniel and Harth, Philipp and Macke, Jakob H. and Hege, Hans-Christian and de Kock, Christiaan P. J. and Sakmann, Bert and Oberlaender, Marcel}, title = {A Theory for the Emergence of Neocortical Network Architecture}, series = {BioRxiv}, journal = {BioRxiv}, doi = {https://doi.org/10.1101/2020.11.13.381087}, language = {en} }