Journal of Digital Imaging

, Volume 19, Issue 2, pp 148–158 | Cite as

LONI Visualization Environment

  • Ivo D. DinovEmail author
  • Daniel Valentino
  • Bae Cheol Shin
  • Fotios Konstantinidis
  • Guogang Hu
  • Allan MacKenzie-Graham
  • Erh-Fang Lee
  • David Shattuck
  • Jeff Ma
  • Craig Schwartz
  • Arthur W. Toga

Over the past decade, the use of informatics to solve complex neuroscientific problems has increased dramatically. Many of these research endeavors involve examining large amounts of imaging, behavioral, genetic, neurobiological, and neuropsychiatric data. Superimposing, processing, visualizing, or interpreting such a complex cohort of datasets frequently becomes a challenge. We developed a new software environment that allows investigators to integrate multimodal imaging data, hierarchical brain ontology systems, on-line genetic and phylogenic databases, and 3D virtual data reconstruction models. The Laboratory of Neuro Imaging visualization environment (LONI Viz) consists of the following components: a sectional viewer for imaging data, an interactive 3D display for surface and volume rendering of imaging data, a brain ontology viewer, and an external database query system. The synchronization of all components according to stereotaxic coordinates, region name, hierarchical ontology, and genetic labels is achieved via a comprehensive BrainMapper functionality, which directly maps between position, structure name, database, and functional connectivity information. This environment is freely available, portable, and extensible, and may prove very useful for neurobiologists, neurogenetisists, brain mappers, and for other clinical, pedagogical, and research endeavors.

Key words

Software ontology brain atlas visualization gene mapping 



Many individuals have contributed to the development effort over the past several years that led to the design, implementation, debugging, and validation of the LONI Viz environment—most notably Seth W. Ruffins, Russell E. Jacobs, Jianming Hu, Jason Landerman, and Hui Wang was invaluable in the past four critical version releases. This research is supported by grants from NIA P50 AG16570, K08 AG100784; NLM R01 2R01 LM05639-06; NIH/NCRR 2 P41 RR13642 and NIH/NIMH 5 P01 MN52176, NSF DUE 0442992, NIH/NCBC U52 RR021813.


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Copyright information

© SCAR (Society for Computer Applications in Radiology) 2006

Authors and Affiliations

  • Ivo D. Dinov
    • 1
    • 2
    • 4
    Email author
  • Daniel Valentino
    • 1
    • 3
  • Bae Cheol Shin
    • 1
  • Fotios Konstantinidis
    • 1
  • Guogang Hu
    • 1
  • Allan MacKenzie-Graham
    • 1
  • Erh-Fang Lee
    • 1
  • David Shattuck
    • 1
  • Jeff Ma
    • 1
  • Craig Schwartz
    • 1
  • Arthur W. Toga
    • 1
  1. 1.Center for Computational Biology and Laboratory of Neuro Imaging, Department of NeurologyUCLALos AngelesUSA
  2. 2.Department of StatisticsUCLALos AngelesUSA
  3. 3.Department of RadiologyUCLALos AngelesUSA
  4. 4.Center for Computational BiologyUCLA David Geffen School of MedicineLos AngelesUSA

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