Neuronale Informationsverarbeitung

Confocal Microscopy: Semi-Automatic Segmentation, Tracing and Analysis of 3D Images

In this project we developed algorithms for the computer assisted segmentation and 3D-reconstruction of neurons from confocal microscope image stacks. We investigated methods for the correction of scaling artifacts due to refractive index mismatch and tissue shrinking. We also developed blind  deconvolution techniques in order to comensate for the strongly anisotropic point-spread functions measured in the stained preparations.  Deconvolution techniques were validated in preparations of optic neurpils where the resolution of the confocal microscope scans could be sufficiently enhanced in order to study colocalization between synaptic vesicle markers near the resolution limit of light. We evaluated techniques based on the wavelet transform for increasing the signal-to-noise ratio of the confocal images, and we developed semi-automatic algorithms for segmentation, tracing and reconstruction of connected tubular structures. 3D-reconstruction techniques were  evaluated on 3D scans of neurons from Maduca Sexta.  <br /><br />Acknowledgement: Research was funded by BMBF, DFG, and the Technische Universität Berlin.