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TU Berlin

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Analysis of Neural Data

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Automatic Segmentation and Skeletonization of Neurons from Confocal Microscopy Images Based on the 3-D Wavelet Transform
Citation key Dima2003b
Author Dima, A. and Scholz, M. and Obermayer, K.
Pages 790-801
Year 2003
DOI 10.1117/1.1526102
Journal IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 11
Number 7
Abstract In this work, we focus on methods for the preprocessing of neurons from three-dimensional (3-D) confocal microscopy images, which are needed for a subsequent detailed morphologic analysis. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches to guarantee meaningful results: 1) a reliable segmentation of objects of different sizes independent of image contrast, and, based on it, 2) the computation of skeleton points along the branch central axes, and 3) the reliable detection of branching points and of problematic regions. These are preprocessing steps to gather information which is needed by the subsequent construction of a graph representing the geometry of the neuron and a final surface reconstruction.
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