KAUST Research Workshop on Innovative Technologies to Study Brain Energy Metabolism
King Abdullah University of Science & Technology, Saudi Arabia
Markus Hadwiger is an Associate Professor in Computer Science and the Visual Computing Center (VCC) at KAUST, which he joined in October 2009. He leads the High-Performance Visualization research group at VCC, where his research interests in the area of scientific visualization include extreme-scale visual computing and visualization, volume visualization, medical visualization, large-scale image and volume processing, multi-resolution techniques, data streaming and out-of-core processing, interactive segmentation, and GPU algorithms and architecture. He is a co-author of the book Real-Time Volume Graphics published in 2006 and has been involved in many courses and tutorials about volume rendering and visualization at ACM SIGGRAPH, ACM SIGGRAPH Asia, IEEE Visualization, and Eurographics. Prof. Hadwiger has co-authored more than 60 refereed articles.
This talk will give an overview of how interactive visualization can help with exploring, analyzing, and understanding high-resolution neuroscience data. We will first describe the design of ConnectomeExplorer, which is an application for the interactive exploration and query-guided visual analysis of large volumetric electron microscopy data. We have developed an interactive query system that supports the specification of dynamically evaluated queries, which allows posing and answering domain-specific questions in an intuitive manner. We will further describe the design of Abstractocyte, which is a system for the visual analysis of astrocytes and their relation to neurons. The morphology of astrocytes can be explored using various visual abstraction levels, while simultaneously analyzing neighboring neurons and their connectivity. This is enabled by a conceptual abstraction space for jointly visualizing astrocytes and neurons at different abstraction levels, with smooth transitions between different abstractions. In contrast to simply switching between different visualizations, this preserves the visual context and correlations throughout the transition. In addition to investigating astrocytes, neurons, and their relationships, we enable the interactive analysis of the distribution of glycogen.