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

被引:108
作者
Brown, Kerry M. [1 ]
Barrionuevo, German [2 ]
Canty, Alison J. [3 ]
De Paola, Vincenzo [3 ]
Hirsch, Judith A. [4 ]
Jefferis, Gregory S. X. E. [5 ]
Lu, Ju [6 ]
Snippe, Marjolein [3 ]
Sugihara, Izumi [7 ]
Ascoli, Giorgio A. [1 ]
机构
[1] George Mason Univ, Krasnow Inst Adv Study, Fairfax, VA 22030 USA
[2] Univ Pittsburgh, Dept Neurosci, Pittsburgh, PA USA
[3] Univ London Imperial Coll Sci Technol & Med, MRC Clin Sci Ctr, London, England
[4] Univ So Calif, Dept Biol Sci, Los Angeles, CA 90089 USA
[5] MRC Lab Mol Biol, Div Neurobiol, Cambridge, England
[6] Stanford Univ, Dept Biol Sci, James H Clark Ctr Biomed Engn & Sci, Stanford, CA 94305 USA
[7] Tokyo Med & Dent Univ, Sch Med, Dept Syst Neurophysiol, Tokyo 113, Japan
关键词
Axons; Dendrites; Neuroanatomy; Tracing; High-throughput; Morphometry; Optical imaging; VISUAL-CORTEX; QUANTITATIVE MORPHOMETRY; IN-VIVO; NEOCORTEX; CELLS; TOOL; INTERNEURONS; PROJECTIONS; INTEGRATION; PLASTICITY;
D O I
10.1007/s12021-010-9095-5
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:143 / 157
页数:15
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