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BrainGazer - Visual Queries for Neurobiology Research

S. Bruckner, V. Šoltészová, M. E. Gröller, J. H. u, K. Bühler, J. Yu, and B. Dickson

Abstract

Neurobiology investigates how anatomical and physiological relationships in the nervous system mediate behavior. Molecular genetic techniques, applied to species such as the common fruit fly Drosophila melanogaster, have proven to be an important tool in this research. Large databases of transgenic specimens are being built and need to be analyzed to establish models of neural information processing. In this paper we present an approach for the exploration and analysis of neural circuits based on such a database. We have designed and implemented BrainGazer, a system which integrates visualization techniques for volume data acquired through confocal microscopy as well as annotated anatomical structures with an intuitive approach for accessing the available information. We focus on the ability to visually query the data based on semantic as well as spatial relationships. Additionally, we present visualization techniques for the concurrent depiction of neurobiological volume data and geometric objects which aim to reduce visual clutter. The described system is the result of an ongoing interdisciplinary collaboration between neurobiologists and visualization researchers.

S. Bruckner, V. Šoltészová, M. E. Gröller, J. H. u, K. Bühler, J. Yu, and B. Dickson, "BrainGazer - Visual Queries for Neurobiology Research," IEEE Transactions on Visualization and Computer Graphics, vol. 15, iss. 6, p. 1497–1504, 2009. doi:10.1109/TVCG.2009.121
[BibTeX]

Neurobiology investigates how anatomical and physiological relationships in the nervous system mediate behavior. Molecular genetic techniques, applied to species such as the common fruit fly Drosophila melanogaster, have proven to be an important tool in this research. Large databases of transgenic specimens are being built and need to be analyzed to establish models of neural information processing. In this paper we present an approach for the exploration and analysis of neural circuits based on such a database. We have designed and implemented BrainGazer, a system which integrates visualization techniques for volume data acquired through confocal microscopy as well as annotated anatomical structures with an intuitive approach for accessing the available information. We focus on the ability to visually query the data based on semantic as well as spatial relationships. Additionally, we present visualization techniques for the concurrent depiction of neurobiological volume data and geometric objects which aim to reduce visual clutter. The described system is the result of an ongoing interdisciplinary collaboration between neurobiologists and visualization researchers.
@ARTICLE {Bruckner-2009-BVQ,
author = "Stefan Bruckner and Veronika \v{S}olt{\'e}szov{\'a} and Meister Eduard Gr{\"o}ller and Ji\v{r}{\'i} Hlad\r{u}vka and Katja B{\"u}hler and Jai Yu and Barry Dickson",
title = "BrainGazer - Visual Queries for Neurobiology Research",
journal = "IEEE Transactions on Visualization and Computer Graphics",
year = "2009",
volume = "15",
number = "6",
pages = "1497--1504",
month = "nov",
abstract = "Neurobiology investigates how anatomical and physiological relationships  in the nervous system mediate behavior. Molecular genetic techniques,  applied to species such as the common fruit fly Drosophila melanogaster,  have proven to be an important tool in this research. Large databases  of transgenic specimens are being built and need to be analyzed to  establish models of neural information processing. In this paper  we present an approach for the exploration and analysis of neural  circuits based on such a database. We have designed and implemented  BrainGazer, a system which integrates visualization techniques for  volume data acquired through confocal microscopy as well as annotated  anatomical structures with an intuitive approach for accessing the  available information. We focus on the ability to visually query  the data based on semantic as well as spatial relationships. Additionally,  we present visualization techniques for the concurrent depiction  of neurobiological volume data and geometric objects which aim to  reduce visual clutter. The described system is the result of an ongoing  interdisciplinary collaboration between neurobiologists and visualization  researchers.",
pdf = "pdfs/Bruckner-2009-BVQ.pdf",
images = "images/Bruckner-2009-BVQ.jpg",
thumbnails = "images/Bruckner-2009-BVQ.png",
youtube = "https://www.youtube.com/watch?v=LB5t3RtLifk",
affiliation = "tuwien",
doi = "10.1109/TVCG.2009.121",
event = "IEEE Visualization 2009",
keywords = "biomedical visualization, neurobiology, visual queries, volume visualization",
location = "Atlantic City, New Jersey, USA",
url = "//www.cg.tuwien.ac.at/research/publications/2009/bruckner-2009-BVQ/"
}
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