title: Automated reconstruction of neuronal morphology based on local geometrical and global structural models.
abstract: Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets.
authors.affiliation: Qiushi Academy for Advanced Studies, Zhejiang University, 38 ZheDa Road, Hangzhou 310027, China. tingzhao@gmail.com
authors.forename: Ting
authors.initials: T
authors.lastname: Zhao
authors.forename: Jun
authors.initials: J
authors.lastname: Xie
authors.forename: Fernando
authors.initials: F
authors.lastname: Amat
authors.forename: Nathan
authors.initials: N
authors.lastname: Clack
authors.forename: Parvez
authors.initials: P
authors.lastname: Ahammad
authors.forename: Hanchuan
authors.initials: H
authors.lastname: Peng
authors.forename: Fuhui
authors.initials: F
authors.lastname: Long
authors.forename: Eugene
authors.initials: E
authors.lastname: Myers
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000639:trends; D021621:Imaging, Three-Dimensional / Q000379:methods* / Q000639:trends; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology* / Q000502:physiology; D012984:Software / Q000639:trends*; D012985:Software Design; D012986:Software Validation