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V. Soltészová:
"Visual Queries in Neuronal Data Exploration";
Betreuer/in(nen): E. Gröller, St. Bruckner; Institut für Computergraphik und Algorithmen, 2010.

The major goal of neuroscientists´ work is to explain specific behavior of living beings, especially humans. However, human behavioral traits are complex and difficult to comprehend. For this purpose, the researchers explore the anatomy and morphology of neuronal circuits of simpler species to identify their meaning and functionality. The fruit fly Drosophila melanogaster is a favorite organism in neurobiology research because it facilitates studies of complex systems on a simple model. For this purpose, large databases of neuronal structures acquired by microscopy scans were built and adapted for computer-aided exploration and visualization. Commodity products feature standard visualization techniques tailored for exploration of biological structures. However, orientation in large collections of structures still poses a problem. Traditional table-view database interfaces allow filtering of items and accessing known subsets of data, but do not support selection based on spatial relationships. In this thesis, we address this problem in the following way. We describe a system which facilitates visual exploration of a large collection of neuroanatomical structures. We combined standard visualization techniques with a novel visual approach for exploration and queries. Our system provides three basic types of queries. Path queries use an intuitive sketching interface and give access to structures located in the proximity of the sketched path. Object queries select objects based on their mutual spatial distance. Semantic queries allow fast browsing using semantic relationships stored in the database. The system was designed in an interdisciplinary collaboration with domain experts, who affirmed that availability of such a system would be very useful for their research.

http://publik.tuwien.ac.at/files/PubDat_194862.pdf