Fully automated segmentation and characterization of the dendritic trees of retinal horizontal neurons

We introduce a new fully automated method for segmenting and characterizing the dendritic tree of neurons in confocal image stacks. Our method is aimed at wide-field-of-view, low-resolution imagery of retinal neurons in which dendrites can be intertwined and difficult to follow. The approach is based on 3-D skeletonization and includes a method for automatically determining an appropriate global threshold as well as a soma detection algorithm. We provide the details of the algorithm and a qualitative performance comparison against a commercially available neurite tracing software package, showing that a segmentation produced by our method more closely matches the ground-truth segmentation.