Automated tracing and segmentation tool for migrating neurons in 4D confocal imagery

Accurate tracing and segmentation of subcellular components of migrating neurons in confocal image sequences are prerequisite steps in many neurobiology studies to understand the biological machinery behind the movement of developing neurons. In this paper, we present an automated tracking, tracing, and segmentation tool for soma, leading, and trailing process of migrating neurons in time-lapse image stacks acquired with a confocal fluorescence microscope. In our approach, we first localize each neuron in the maximum intensity projection of the first frame using manual labeling of the soma and end points of the leading and trailing process. By using each soma position at the first frame, we automatically track the somas in rest of the frames. Then, leading and trailing process are traced in each frame from the soma center to the labeled end tip of the process by using fast marching algorithm. Finally, the soma, leading and trailing processes of each neuron are segmented by using the soma center and traces as seed points, and their boundaries are separated from each other. Based on qualitative results, we demonstrate the capability to automatically track, trace, and segment the soma, leading, and trailing processes of a migrating neuron with minimal user input.