Towards automatic reconstruction of axonal structures in volumetric microscopy images depicting only active synapses

We propose an algorithm for the three-dimensional (3D) reconstruction of axonal structures to allow for the correlation of axonal structure, individual synaptic activity and single molecule tracking. In contrast to related works, only active synapses are stained in our acquisitions and the axonal structure is only visible by autofluorescence. We tackle this problem by detection of the medial axis line in the two-dimensional (2D) intensity projection of the 3D image and reconstruction of the 3D structure by axial interpolation between connected active synapses. Due to the noncontinuous staining, the detection of the medial axis line cannot rely on a global tree like structure. Instead, we compute an initial skeleton by global segmentation and expand it by iteratively adding line segments that are locally optimal according to the model knowledge of an axon. We evaluate our algorithm against a ground truth computed from co-transfection of surface molecules that result in reliable continuous staining of the axonal structure.