3D object retrieval in an atlas of neuronal structures
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O R I G I N A L A RT I C L E
3D object retrieval in an atlas of neuronal structures M. Trapp · F. Schulze · K. Bühler · T. Liu · B.J. Dickson
Published online: 19 September 2013 © Springer-Verlag Berlin Heidelberg 2013
Abstract Circuit neuroscience tries to solve one of the most challenging questions in biology: How does the brain work? An important step toward an answer to this question is to gather detailed knowledge about the neuronal circuits of the model organism Drosophila melanogaster. Geometric representations of neuronal objects of the Drosophila are acquired using molecular genetic methods, confocal microscopy, nonrigid registration and segmentation. These objects are integrated into a constantly growing common atlas. The comparison of new segmented neuronal objects to already known neuronal structures is a frequent task, which evolves with a growing amount of data into a bottleneck of the knowledge discovery process. Thus, the exploration of the atlas by means of domain specific similarity measures becomes a pressing need. To enable similarity based retrieval of neuronal objects, we defined together with domain experts tailored dissimilarity measures for each of the three typical neuronal structures cell body, projection, and arborization. Moreover, we defined the neuron enhanced similarity for projections and arborizations. According to domain experts, the developed system has big advantages for all tasks, which involve extensive data exploration. Keywords 3D object retrieval · Neuronal structures · Drosophila melanogaster · Domain specific similarity measures
M. Trapp (B) · F. Schulze · K. Bühler VRVis Forschungs GmbH, Vienna, Austria e-mail: [email protected] T. Liu · B.J. Dickson Institute of Molecular Pathology, Vienna, Austria
1 Introduction A mechanistic understanding of brain function must ultimately be built upon a detailed account of how individual neurons are organized into functional circuits, and how information processing within these circuits generates perception and behavior. Genetic model organisms offer the possibility of applying powerful genetic methods to identify, characterize, and manipulate specific neurons in the brain. In particular, Drosophila melanogaster, the fruit fly, has emerged as one of the leading model systems for exploring how information processing in defined neural circuits generates complex behavioral patterns [20]. Central to these approaches are methods to reproducibly label and identify cells of a given type, and to construct digital atlases that ideally would include representations of each neuronal type on a common frame of reference. Molecular genetic methods make it possible to express transgenic markers in various neuronal subsets. In some cases, individual types of neurons can be labeled in this manner, though more often multiple cell types are labeled in each brain. Neurons marked in this manner can be visualized using confocal microscopy, resulting in multichannel volumetric images. To be able to combine images of different fruit flies, i.e., to overcome
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