M-AMST: an automatic 3D neuron tracing method based on mean shift and adapted minimum spanning tree
作者: Zhijiang WanYishan HeMing HaoJian YangNing Zhong
作者单位: 1Beijing University of Technology
2Maebashi Institute of Technology
3Beijing Key Laboratory of MRI and Brain Informatics
4Beijing International Collaboration Base on Brain Informatics and Wisdom Services
5Beijing Internation
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Journal
DOI: 10.1186/s12859-017-1597-9
关键词: M-AMSTNeuron reconstructionMean shiftSphere modelCoordinate transformation
英文摘要: Understanding the working mechanism of the brain is one of the grandest challenges for modern science. Toward this end, the BigNeuron project was launched to gather a worldwide community to establish a big data resource and a set of the state-of-the-art of single neuron reconstruction algorithms. Many groups contributed their own algorithms for the project, including our mean shift and minimum spanning tree (M-MST). Although M-MST is intuitive and easy to implement, the MST just considers spatial information of single neuron and ignores the shape information, which might lead to less precise connections between some neuron segments. In this paper, we propose an improved algorithm, namely M-AMST, in which a rotating sphere model based on coordinate transformation is used to improve the...
原始语种摘要: Understanding the working mechanism of the brain is one of the grandest challenges for modern science. Toward this end, the BigNeuron project was launched to gather a worldwide community to establish a big data resource and a set of the state-of-the-art of single neuron reconstruction algorithms. Many groups contributed their own algorithms for the project, including our mean shift and minimum spanning tree (M-MST). Although M-MST is intuitive and easy to implement, the MST just considers spatial information of single neuron and ignores the shape information, which might lead to less precise connections between some neuron segments. In this paper, we propose an improved algorithm, namely M-AMST, in which a rotating sphere model based on coordinate transformation is used to improve the...
全文获取路径: Springer  (合作)
分享到:
来源刊物:
影响因子:3.024 (2012)

×
关键词翻译
关键词翻译
  • spanning 生成
  • automatic 自动的
  • tracing 透写
  • shift 变位
  • reconstruction 复原
  • intuitive 直观的
  • community 群落
  • transformation 变换
  • shape 形状
  • coordinate 坐标