Detection of presynaptic terminals on dendritic spines in double labeling confocal images

For the analysis of learning processes and the underlying changes of the shape of excitatory synapses (spines), 3-D volume samples of selected dendritic segments are scanned by a confocal laser scanning microscope. The images are unsharp because of the (direction dependent) resolution limit. A deconvolution on image data is not sufficient for the resolution needed. Therefore a parametric model is used to reconstruct the dendrite and the spines. The parameter estimation of model is done in a two step approach. First, rough center axes of dendrite and spines are found by a growing model which can be adjusted interactively. In a second step the model parameters are optimized during an iterative process. To estimate the deviation between the microscope image and the model, the model is sampled with the same resolution as the microscope image and convolved by the microscope point spread function (psf). The result is a accurate model of dendrite and spines. The model fitting process is comp...

• Type: Conference
• Year: 2006
• Where: ICPR
• Authors: Andreas Herzog, Bernd Michaelis, Gerald Krell, Katharina Braun, Robert Niese, Wladimir Ovtscharoff
• Keywords: Computer Vision, Geometrical Model, ICPR 2006, Model Fitting Process, Model Parameters