title: Anisotropic path searching for automatic neuron reconstruction.
abstract: Full reconstruction of neuron morphology is of fundamental interest for the analysis and understanding of their functioning. We have developed a novel method capable of automatically tracing neurons in three-dimensional microscopy data. In contrast to template-based methods, the proposed approach makes no assumptions about the shape or appearance of neurite structure. Instead, an efficient seeding approach is applied to capture complex neuronal structures and the tracing problem is solved by computing the optimal reconstruction with a weighted graph. The optimality is determined by the cost function designed for the path between each pair of seeds and by topological constraints defining the component interrelations and completeness. In addition, an automated neuron comparison method is introduced for performance evaluation and structure analysis. The proposed algorithm is computationally efficient and has been validated using different types of microscopy data sets including Drosophila's projection neurons and fly neurons with presynaptic sites. In all cases, the approach yielded promising results.
authors.affiliation: Janelia Farm Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA. xiejun3g@gmail.com
authors.forename: Jun
authors.initials: J
authors.lastname: Xie
authors.forename: Ting
authors.initials: T
authors.lastname: Zhao
authors.forename: Tzumin
authors.initials: T
authors.lastname: Lee
authors.forename: Eugene
authors.initials: E
authors.lastname: Myers
authors.forename: Hanchuan
authors.initials: H
authors.lastname: Peng
mesh_terms: D000465:Algorithms; D000818:Animals; D016880:Anisotropy; D004330:Drosophila; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008853:Microscopy / Q000379:methods*; D009474:Neurons / Q000166:cytology*; D010363:Pattern Recognition, Automated / Q000379:methods*