ConnectomeExplorer: Query-Guided Visual Analysis of Large Volumetric Neuroscience Data

Johanna Beyer, Ali K. Al-Awami, Narayanan Kasthuri, Jeff W. Lichtman, Hanspeter Pfister and Markus Hadwiger

ConnectomeExplorer: Query-Guided Visual Analysis of Large Volumetric Neuroscience Data
IEEE Transactions on Visualization and Computer Graphics, Vol.19, No.12 (Proceedings IEEE Scientific Visualization 2013), pp. 2868-2877 , 2013

This paper presents ConnectomeExplorer, an application for the interactive exploration and query-guided visual analysis of large volumetric electron microscopy (EM) data sets in connectomics research. Our system incorporates a knowledge-based query algebra that supports the interactive specification of dynamically evaluated queries, which enable neuroscientists to pose and answer domain-specific questions in an intuitive manner. Queries are built step by step in a visual query builder, building more complex queries from combinations of simpler queries. Our application is based on a scalable volume visualization framework that scales to multiple volumes of several teravoxels each, enabling the concurrent visualization and querying of the original EM volume, additional segmentation volumes, neuronal connectivity, and additional meta data comprising a variety of neuronal data attributes. We evaluateour application on a data set of roughly one terabyte of EM data and 750 GB of segmentation data, containing over 4,000 segmented stuctures and 1,000 synapses. We demonstrate typical use-case scenarios of our collaborators in neuroscience, where our system has enabled them to answer specific scientific questions using interactive querying and analysis on the full-size data for the first time.

@article{Beyer2013ConnectomeExplorer,
 title = {ConnectomeExplorer: Query-Guided Visual Analysis of Large Volumetric Neuroscience Data},
 author = {Beyer, Johanna and Al-Awami, Ali K. and Kasthuri, Narayanan and Lichtman, Jeff W. and Pfister, Hanspeter and Hadwiger, Markus},
 journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE Scientific Visualization 2013)},
 year = {2013},
 volume = {19},
 number = {12},
 pages = {2868--2877}
}