Neuron anatomy structure reconstruction based on a sliding filter.
BACKGROUND
Reconstruction of neuron anatomy structure is a challenging and important task in neuroscience. However, few algorithms can automatically reconstruct the full structure well without manual assistance, making it essential to develop new methods for this task.


METHODS
This paper introduces a new pipeline for reconstructing neuron anatomy structure from 3-D microscopy image stacks. This pipeline is initialized with a set of seeds that were detected by our proposed Sliding Volume Filter (SVF), given a non-circular cross-section of a neuron cell. Then, an improved open curve snake model combined with a SVF external force is applied to trace the full skeleton of the neuron cell. A radius estimation method based on a 2D sliding band filter is developed to fit the real edge of the cross-section of the neuron cell. Finally, a surface reconstruction method based on non-parallel curve networks is used to generate the neuron cell surface to finish this pipeline.


RESULTS
The proposed pipeline has been evaluated using publicly available datasets. The results show that the proposed method achieves promising results in some datasets from the DIgital reconstruction of Axonal and DEndritic Morphology (DIADEM) challenge and new BigNeuron project.


CONCLUSIONS
The new pipeline works well in neuron tracing and reconstruction. It can achieve higher efficiency, stability and robustness in neuron skeleton tracing. Furthermore, the proposed radius estimation method and applied surface reconstruction method can obtain more accurate neuron anatomy structures.
Research Center of Perception and Computing, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. luogongning@hit.edu.cn.
Gongning
G
Luo
Research Center of Perception and Computing, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. suidong10@gmail.com.
Dong
D
Sui
Research Center of Perception and Computing, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. wangkq@hit.edu.cn.
Kuanquan
K
Wang
Department of Computer Science and Engineering, Incheon National University, Incheon, Korea. jschae@inu.ac.kr.
Jinseok
J
Chae
D000465:Algorithms; D006801:Humans; D021621:Imaging, Three-Dimensional; D008853:Microscopy; D009474:Neurons / Q000737:chemistry / Q000473:pathology*