Automated Axon Tracking of 3D Confocal Laser Scanning ...

1. IntroductionThe orientation of motor axons is critical in answering questions regarding synapse eliminationin a developing muscle (Keller-Peck et al., 2001). Biologists have tried to address this issue byidentifying the post-synaptic targets using transgenic mice that express fluorescent proteins insmall subsets of motor axons. The post-synaptic targets are the cells innervated by the axons.More specifically, in the neuromuscular system, these are the muscle fibers. At neuromuscularjunctions of developing mammals, the developing axonal branches of several motor neuronscompete with each other resulting in withdrawal of all branches but one (Kasthuri et al., 2003).The biological application of the developed algorithm is to reconstruct the entire innervationfield within a skeletal muscle based on images acquired from confocal microscopy. Given a 3Dimage stack with non-uniform resolution in the x-, y- and z-direction, it is desirable to segmentmultiple axons contained in the neuron image and reduce them to one-pixel wide medial axis.Our aim here is to better understand the spatial relations of groups of axons traveling in a nerve.The features revealed by the reconstruction help neuroscientists to understand how neuronsinteract with and control muscular retracting. The size of the individual datasets range from 20-30 Megabytes, but when they are joined together to form a collage, they are typically a fewTerabytes in size. Since the data sets to be analyzed are huge, robust and automated algorithmsare needed to track the centerlines of the axons accurately.The tracking approaches introduced in the past can be broadly classified into three groups.The first class of algorithms tracks the centerlines of tubular objects in the Maximum IntensityProjection (MIP) image. As the name suggests, the MIP image along a certain direction is theprojection of maximum intensities in the dataset along that direction onto a plane perpendicularto it. This is essentially a data reduction step which provides a 2D image of the objects present in3