Neuroinformatics

, Volume 9, Issue 2, pp 143–157

The DIADEM Data Sets: Representative Light Microscopy Images of Neuronal Morphology to Advance Automation of Digital Reconstructions

  • Kerry M. Brown
  • Germán Barrionuevo
  • Alison J. Canty
  • Vincenzo De Paola
  • Judith A. Hirsch
  • Gregory S. X. E. Jefferis
  • Ju Lu
  • Marjolein Snippe
  • Izumi Sugihara
  • Giorgio A. Ascoli
Mini-Review

DOI: 10.1007/s12021-010-9095-5

Cite this article as:
Brown, K.M., Barrionuevo, G., Canty, A.J. et al. Neuroinform (2011) 9: 143. doi:10.1007/s12021-010-9095-5

Abstract

The comprehensive characterization of neuronal morphology requires tracing extensive axonal and dendritic arbors imaged with light microscopy into digital reconstructions. Considerable effort is ongoing to automate this greatly labor-intensive and currently rate-determining process. Experimental data in the form of manually traced digital reconstructions and corresponding image stacks play a vital role in developing increasingly more powerful reconstruction algorithms. The DIADEM challenge (short for DIgital reconstruction of Axonal and DEndritic Morphology) successfully stimulated progress in this area by utilizing six data set collections from different animal species, brain regions, neuron types, and visualization methods. The original research projects that provided these data are representative of the diverse scientific questions addressed in this field. At the same time, these data provide a benchmark for the types of demands automated software must meet to achieve the quality of manual reconstructions while minimizing human involvement. The DIADEM data underwent extensive curation, including quality control, metadata annotation, and format standardization, to focus the challenge on the most substantial technical obstacles. This data set package is now freely released (http://diademchallenge.org) to train, test, and aid development of automated reconstruction algorithms.

Keywords

AxonsDendritesNeuroanatomyTracingHigh-throughputMorphometryOptical imaging

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Kerry M. Brown
    • 1
  • Germán Barrionuevo
    • 2
  • Alison J. Canty
    • 3
    • 8
  • Vincenzo De Paola
    • 3
  • Judith A. Hirsch
    • 4
  • Gregory S. X. E. Jefferis
    • 5
  • Ju Lu
    • 6
  • Marjolein Snippe
    • 3
    • 9
  • Izumi Sugihara
    • 7
  • Giorgio A. Ascoli
    • 1
  1. 1.Krasnow Institute for Advanced StudyGeorge Mason UniversityFairfaxUSA
  2. 2.Department of NeuroscienceUniversity of PittsburghPittsburghUSA
  3. 3.MRC Clinical Sciences CentreImperial College LondonLondonUK
  4. 4.Department of Biological SciencesUniversity of Southern CaliforniaLos AngelesUSA
  5. 5.Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUK
  6. 6.Department of Biological Sciences, James H. Clark Center for Biomedical Engineering and SciencesStanford UniversityStanfordUSA
  7. 7.Department of Systems NeurophysiologyTokyo Medical and Dental University School of MedicineTokyoJapan
  8. 8.School of MedicineUniversity of TasmaniaHobartAustralia
  9. 9.Blizard Institute of Cell and Molecular ScienceQueen Mary University of LondonLondonUK