Herr Hennes Rave, Institut für Informatik

Current PublicationsPeivandi, Armin Darius; Holtkamp, Michael; Rave, Hennes; Linsen, Lars; Martens, Sven; Müller, Klaus-Michael; Karst, Uwe; Martens, Sabrina Rapid versus slow degeneration and complications of biomaterials in patients with congenital heart disease. Cardiovascular Pathology Vol. 75, 2025 online
Molchanov, Vladimir; Rave, Hennes; Linsen, Lars Efficient Regularization-based Normalization for Interactive Multidimensional Data Analysis Without Scaling Artifacts. Journal of WSCG Vol. 33 (1), 2025 online
Kronenberg, Katharina; Rave, Hennes; Ghaffari-Tabrizi-Wizsy, Nassim; Nyckees, Danae; Elinkmann, Matthias; Freitak, Dalial; Linsen, Lars; Gonzalez de Vega, Raquel; Clases, David Exploring high-dimensional LA-ICP-TOFMS data with uniform manifold approximation and projection (UMAP). Journal of Analytical Atomic Spectrometry Vol. 0, 2025 online
Molchanov, Vladimir*; Rave, Hennes*; Linsen, Lars A Decluttering Lens for Scatterplots. , 2025 online
Cutura, Rene; Rave, Hennes; Ngo, Quynh Quang; Molchanov, Vladimir; Linsen, Lars; Weiskopf, Daniel; Sedlmair, Michael SiGrid: Gridifying Scatterplots with Sector-Based Regularization and Hagrid. , 2025 online
Rave, Hennes; Molchanov, Vladimir; Linsen, Lars De-cluttering Scatterplots with Integral Images. IEEE Transactions on Visualization and Computer Graphics Vol. 0 (0), 2024 online
Rave, Hennes; Evers, Marina; Gerrits, Tim; Linsen, Lars Region-based Visualization in Hierarchically Clustered Ensemble Volumes. , 2024 online
Evers, Marina; Leistikow, Simon; Rave, Hennes; Linsen, Lars Interactive Visual Analysis of Spatial Sensitivities. IEEE Transactions on Visualization and Computer Graphics Vol. 0 (0), 2024 online
Rave, Hennes; Molchanov, Vladimir; Linsen, Lars Uniform Sample Distribution in Scatterplots via Sector-based Transformation. , 2024 online
Current ProjectsCRC 1450 - Z01: Interactive and computational analysis of large multiscale imaging data

The multiscale imaging strategy central to this initiative imposes novel data analysis challenges. The high complexity of the acquired data results from their nature of being volumetric, time-varying, large, multiscale, and forming cohorts). Meeting these challenges requires basic research in the fields of image analysis, machine learning, and visualization. Machine learning will be used to uncover inherent relationships between patterns at multiple scales. An interactive visual approach supports the user-centric analysis of detected features.

The deliverable of this project will be generally applicable, effective, and efficient methods supporting the overall goal of multiscale data analysis.

online
E-Mailhennes.rave@uni-muenster.de
Phone+49 251 83-33751
Room605
Secretary   Sekretariat Sichma
Frau Katharina Sichma
Telefon +49 251 83-32700
Zimmer 604b
AddressHerr Hennes Rave
Institut für Informatik
Fachbereich Mathematik und Informatik der Universität Münster
Einsteinstrasse 62
48149 Münster
Deutschland
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