Three-dimensional neurite tracing under globally varying contrast

We study the 3D neurite tracing problem in different imaging modalities. We consider that the examined images do not provide sufficient contrast between neurite and background, and the signal-to-noise ratio varies spatially. We first split the stack into box sub-volumes, and inside each box we evolve simultaneously a number of different open-curve snakes. The curves deform based on three criteria: local image statistics, local shape smoothness, and a term that enforces pairwise attraction between snakes, given their spatial proximity and shapes. We validate our method using larva Drosophila sensory neurons imaged with confocal laser scanning microscopy, as well as publicly available datasets.