No abstract

No abstract

An accurate neuron reconstruction is very important to understand neuron morphology and function, but it is still a challenging task due to the time consuming of manual tracing and the unsatisfactory accuracy of automatic tracing. One way to address the challenge is generating a reconstruction automatically and then checking and amending the result manually. Aiming at implementing this process efficiently, we propose a pipeline to retrieve substructures on one or more neuron reconstructions, which are very similar to a marked problematic substructure and need to be checked one by one. The pipeline consists of four steps: getting a marked substructure, constructing a query substructure, generating candidate substructures and retrieving most similar substructures. The retrieval procedure was tested on 163 gold standard reconstructions provided by the BigNeuron project and a reconstruction of a mouse’s large neuron. Experimental results showed that the implementation of the proposed methods is very efficient and all retrieved substructures are very similar to the marked one in numbers of nodes and branches, and degree of curvature.

No abstract