Cargando…
Rapid Reconstruction of 3D Neuronal Morphology from Light Microscopy Images with Augmented Rayburst Sampling
Digital reconstruction of three-dimensional (3D) neuronal morphology from light microscopy images provides a powerful technique for analysis of neural circuits. It is time-consuming to manually perform this process. Thus, efficient computer-assisted approaches are preferable. In this paper, we prese...
Autores principales: | Ming, Xing, Li, Anan, Wu, Jingpeng, Yan, Cheng, Ding, Wenxiang, Gong, Hui, Zeng, Shaoqun, Liu, Qian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877282/ https://www.ncbi.nlm.nih.gov/pubmed/24391966 http://dx.doi.org/10.1371/journal.pone.0084557 |
Ejemplares similares
-
Touching Soma Segmentation Based on the Rayburst Sampling Algorithm
por: Hu, Tianyu, et al.
Publicado: (2017) -
Weakly Supervised Learning of 3D Deep Network for Neuron Reconstruction
por: Huang, Qing, et al.
Publicado: (2020) -
Automated and Accurate Detection of Soma Location and Surface Morphology in Large-Scale 3D Neuron Images
por: Yan, Cheng, et al.
Publicado: (2013) -
Visible rodent brain-wide networks at single-neuron resolution
por: Yuan, Jing, et al.
Publicado: (2015) -
Reconstruction of neuronal morphologies from electron microscopy images using graph cuts
por: Yang, Huei-Fang, et al.
Publicado: (2010)