Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform
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 [7]. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches which are based on multiscale edges [17] 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 [27] and a final surface reconstruction [31].
segmentation skeletonization confocal microscopy across-scales validation branch detection 3-d multiscale curvature 3-d neuronal data 3-d-wavelet edge detection