@misc{PfisterKaynigBothaetal.2012, author = {Pfister, Hanspeter and Kaynig, Verena and Botha, Charl and Bruckner, Stefan and Dercksen, Vincent J. and Hege, Hans-Christian and Roerdink, Jos}, title = {Visualization in Connectomics}, doi = {10.1007/978-1-4471-6497-5_21}, year = {2012}, language = {en} } @incollection{PfisterKaynigBothaetal.2014, author = {Pfister, Hanspeter and Kaynig, Verena and Botha, Charl P. and Bruckner, Stefan and Dercksen, Vincent J. and Hege, Hans-Christian and Roerdink, Jos B.T.M.}, title = {Visualization in Connectomics}, series = {Scientific Visualization - Uncertainty, Multifield, Biomedical, and Scalable Visualization}, booktitle = {Scientific Visualization - Uncertainty, Multifield, Biomedical, and Scalable Visualization}, editor = {Hansen, Charles D. and Chen, Min and Johnson, Christopher R. and Kaufman, Arie E. and Hagen, Hans}, publisher = {Springer}, isbn = {978-1-4471-6496-8}, doi = {10.1007/978-1-4471-6497-5_21}, pages = {221 -- 245}, year = {2014}, abstract = {Connectomics is a branch of neuroscience that attempts to create a connectome, i.e., a complete map of the neuronal system and all connections between neuronal structures. This representation can be used to understand how functional brain states emerge from their underlying anatomical structures and how dysfunction and neuronal diseases arise. We review the current state-of-the-art of visualization and image processing techniques in the field of connectomics and describe a number of challenges. After a brief summary of the biological background and an overview of relevant imaging modalities, we review current techniques to extract connectivity information from image data at macro-, meso- and microscales. We also discuss data integration and neural network modeling, as well as the visualization, analysis and comparison of brain networks.}, language = {en} } @inproceedings{HarthBastTroidletal., author = {Harth, Philipp and Bast, Arco and Troidl, Jakob and Meulemeester, Bjorge and Pfister, Hanspeter and Beyer, Johanna and Oberlaender, Marcel and Hege, Hans-Christian and Baum, Daniel}, title = {Rapid Prototyping for Coordinated Views of Multi-scale Spatial and Abstract Data: A Grammar-based Approach}, series = {Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)}, booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)}, doi = {10.2312/vcbm.20231218}, abstract = {Visualization grammars are gaining popularity as they allow visualization specialists and experienced users to quickly create static and interactive views. Existing grammars, however, mostly focus on abstract views, ignoring three-dimensional (3D) views, which are very important in fields such as natural sciences. We propose a generalized interaction grammar for the problem of coordinating heterogeneous view types, such as standard charts (e.g., based on Vega-Lite) and 3D anatomical views. An important aspect of our web-based framework is that user interactions with data items at various levels of detail can be systematically integrated and used to control the overall layout of the application workspace. With the help of a concise JSON-based specification of the intended workflow, we can handle complex interactive visual analysis scenarios. This enables rapid prototyping and iterative refinement of the visual analysis tool in collaboration with domain experts. We illustrate the usefulness of our framework in two real-world case studies from the field of neuroscience. Since the logic of the presented grammar-based approach for handling interactions between heterogeneous web-based views is free of any application specifics, it can also serve as a template for applications beyond biological research.}, language = {en} }