A novel seeding method based on spatial sliding volume filter for neuron reconstruction

Automatic neuron reconstruction is one of the foremost challenging and important problem in the field of neuroscience. However, none of the prevalent algorithms can automatically reconstruct full anatomy structure. All of these make it is essential of developing new method for the tracing task. This paper introduced a novel seeding method for reconstructing neuron structures from 3-D microscopy images stacks. The protocol was initialized with a set of seeds which were detected by our proposed Sliding Volume Filter. And then the open curve snake was applied to the detected seeds to reconstruct the full structural of neuron cells. Results showed the proposed method exhibited excellent performance with its accuracy compared with traditional method. It is worth noting that the seeding method can clearly benefit for 3-D neuron fiber detection and reconstruction.