The Neuron Reconstruction Algorithm
10:30 - 11:00
Modern microscopic techniques enable imaging of three-dimensional neuron morphologies in intact brain tissue. In principle it is now possible to automatically reconstruct the dendritic branching patterns of neurons from 3D fluorescence image stacks. In practice however, the signal-to-noise ratio can be low, in particular in the case of thin dendrites or axons imaged relatively deep in the tissue. Here we present a nonlinear anisotropic diffusion filter that enhances the signal-to-noise ratio while preserving the original dimensions of the structural elements. The key idea is to use structural information in the raw data — the local moments of inertia — to locally control the strength and direction of diffusion filtering. A cylindrical dendrite, for example, is effectively smoothed only parallel to its longitudinal axis, not perpendicular to it. The filter is a valuable general tool for smoothing cellular processes and is well suited for preparing data for subsequent image segmentation and cell reconstruction.
P. J. Broser, R. Schulte, A. Roth, F. Helmchen, J. Waters, S. Lang, B. Sakmann, G. Wittum: Nonlinear anisotropic diffusion filtering of three-dimensional image data from 2-photon microscopy. Journal of Biomedical Optics 9(6), 1253–1264 (2004)
Queisser, G., H. Bading, M. Wittmann, G. Wittum: Filtering, reconstruction and measurement of the geometry of neuron cell nuclei based on confocal microscopy data, Journal of Biomedical Optics, Jan 2008.
Daniel Jungblut, Andreas Vlachos, Gerlind Schuldt, Nadine Zahn, Thomas Deller, Gabriel Wittum: SpineLab – a Tool for Three Dimensional Cell Morphology Reconstruction. J Biomed Opt., 17(7), (2012)