title: Morphological analysis of dendrites and spines by hybridization of ridge detection with twin support vector machine.
abstract: Dendritic spines are described as neuronal protrusions. The morphology of dendritic spines and dendrites has a strong relationship to its function, as well as playing an important role in understanding brain function. Quantitative analysis of dendrites and dendritic spines is essential to an understanding of the formation and function of the nervous system. However, highly efficient tools for the quantitative analysis of dendrites and dendritic spines are currently undeveloped. In this paper we propose a novel three-step cascaded algorithm-RTSVM- which is composed of ridge detection as the curvature structure identifier for backbone extraction, boundary location based on differences in density, the Hu moment as features and Twin Support Vector Machine (TSVM) classifiers for spine classification. Our data demonstrates that this newly developed algorithm has performed better than other available techniques used to detect accuracy and false alarm rates. This algorithm will be used effectively in neuroscience research.
authors.affiliation: School of Electronic Science and Engineering, Nanjing University, Jiangsu, China; School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China.
authors.forename: Shuihua
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Neurology, Northwestern University School of Medicine, Chicago, USA; State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
authors.forename: Mengmeng
authors.initials: M
authors.lastname: Chen
authors.affiliation: School of Electronic Science and Engineering, Nanjing University , Jiangsu , China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Li
authors.affiliation: School of Psychology, Nanjing Normal University , Nanjing, Jiangsu , China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Shao
authors.affiliation: School of Computer Science and Technology, Nanjing Normal University , Nanjing , Jiangsu , China.
authors.forename: Yudong
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: School of Electronic Science and Engineering, Nanjing University , Jiangsu , China.
authors.forename: Sidan
authors.initials: S
authors.lastname: Du
authors.affiliation: School of Electronic Science and Engineering, Nanjing University, Jiangsu, China; Department of Neurology, Northwestern University School of Medicine, Chicago, USA; State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
authors.forename: Jane
authors.initials: J
authors.lastname: Wu
keywords: Dendritic spine; Neuron; Ridgelet detection; Twin Support vector machine