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TU Berlin

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

Lupe

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 neuropils 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.

Acknowledgement: Research was funded by BMBF, DFG, and the Technische Universität Berlin.

Selected Publications:

Automatic Segmentation and Skeletonization of Neurons from Confocal Microscopy Images based on the 3D Wavelet Transform
Citation key Dima02
Author Dima, A. and Scholz, M. and Obermayer, K.
Pages 790 – 801
Year 2002
Journal IEEE Trans. on Image Proc.
Volume 11
Bibtex Type of Publication Selected:3dimages
Link to publication Download Bibtex entry

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