Automatic neuron tracing in volumetric microscopy images with anisotropic path searching.
Full reconstruction of neuron morphology is of fundamental interest for the analysis and understanding of neuron function. We have developed a novel method capable of tracing neurons in three-dimensional microscopy data automatically. In contrast to template-based methods, the proposed approach makes no assumptions on the shape or appearance of neuron's body. Instead, an efficient seeding approach is applied to find significant pixels almost certainly within complex neuronal structures and the tracing problem is solved by computing an graph tree structure connecting these seeds. In addition, an automated neuron comparison method is introduced for performance evaluation and structure analysis. The proposed algorithm is computationally efficient. Experiments on different types of data show promising results.
Xie
Jun
J
Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.
Zhao
Ting
T
Lee
Tzumin
T
Myers
Eugene
E
Peng
Hanchuan
H
D000465:Algorithms; D000818:Animals; D016880:Anisotropy; D001185:Artificial Intelligence; D002478:Cells, Cultured; D006801:Humans; 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*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity