From DIADEM to BigNeuron
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EDITORIAL
From DIADEM to BigNeuron Hanchuan Peng 1 & Erik Meijering 2 & Giorgio A. Ascoli 3
Published online: 29 April 2015 # Springer Science+Business Media New York 2015
The three-dimensional (3D) morphology of axons and dendrites is important for many neuroscience studies. Common tasks such as distinguishing and characterizing neuron phenotypes, modeling projection and potential connectivity patterns, and simulating the electrophysiological behavior of single neurons and neuronal networks all depend on accurate knowledge of 3D neuronal morphology. In fact, such tasks often require the morphology to be explicitly and quantitatively described as opposed to simply illustrated by an image stack.1 Therefore a critical first step in many studies is the digital reconstruction of the 3D morphology of neurons from image stacks. Neuron reconstruction methods have evolved over the last 100 years from the 2D hand drawings by Ramón y Cajal and his contemporaries to quantitative tracing of neuron morphologies in 3D with the help of computers. To this day, manual tracing is still the prevailing method
1
Parekh, R., & Ascoli, G. A. (2013). Neuronal morphology goes digital: a research hub for cellular and system neuroscience. Neuron, 77(6), 1017–38.
even for 3D reconstruction. 2 However, manual approaches are prohibitively expensive for analyzing image data approaching the scale of terabytes and thousands of image stacks, let alone mining higher-order patterns in these data. The long-standing need to automate the laborious and subjective manual analysis of light-microscopic and other types of microscopic images has motivated a large number of bioimage informatics efforts.3 The recent advance in imaging throughput, combined with the desire for large-scale computational modeling, has added a sense of urgency to this need. In 2010 a worldwide neuron reconstruction contest named DIADEM (short for Bdigital reconstruction of axonal and dendritic morphology^) was organized by several major institutions as a way to stimulate progress and attract new computational researchers to join the technology development community.4 The goal of DIADEM was to develop algorithms capable of automatically converting stacks of images visualizing the tree-like shape of neuronal axons and dendrites into faithful 3D digital reconstructions. The contest succeeded in stimulating a burst of progress. However, none of the algorithms presented at the finishing stage of DIADEM reached the
* Giorgio A. Ascoli [email protected] Hanchuan Peng [email protected] Erik Meijering [email protected] 1
Allen Institute for Brain Science, Seattle, WA, USA
2
Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands
3
Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
Meijering, E. (2010). Neuron tracing in perspective. Cytometry Part A, 77(7), 693–704. 3 Peng, H., Tang, J., Xiao, H., Bria, A., Zhou, J., Butler, V., Zhou, Z., Gonzalez-Bellido, P. T., Oh, S. W., Chen, J., Mitra, A., Tsien, R. W., Zeng, H., Ascol
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