Since manual tracing is time consuming and the performance of automatic tracing is unstable, it is still a challenging task to generate accurate neuron reconstruction efficiently and effectively. One strategy is generating a reconstruction automatically and then amending its inaccurate parts manually. Aiming at finding inaccurate substructures efficiently, we propose a pipeline to retrieve similar substructures on one or more neuron reconstructions, which are very similar to a marked problematic substructure. 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.

中文翻译：

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在3D神经元重建中检索相似的子结构

由于手动跟踪非常耗时，并且自动跟踪的性能不稳定，因此有效高效地生成精确的神经元重建仍然是一项艰巨的任务。一种策略是自动生成重建，然后手动修改其不准确的零件。为了有效地发现不正确的子结构，我们提出了一种管道，用于在一个或多个神经元重建中检索相似的子结构，这与标记的有问题的子结构非常相似。管道包括四个步骤：获取标记的子结构，构造查询子结构，生成候选子结构以及检索最相似的子结构。在BigNeuron项目提供的163个金标准重建物和小鼠大神经元的重建物上测试了该检索程序。