title: A primal analysis system of brain neurons data.
abstract: It is a very challenging work to classify the 86 billions of neurons in the human brain. The most important step is to get the features of these neurons. In this paper, we present a primal system to analyze and extract features from brain neurons. First, we make analysis on the original data of neurons in which one neuron contains six parameters: room type, X, Y, Z coordinate range, total number of leaf nodes, and fuzzy volume of neurons. Then, we extract three important geometry features including rooms type, number of leaf nodes, and fuzzy volume. As application, we employ the feature database to fit the basic procedure of neuron growth. The result shows that the proposed system is effective.
authors.affiliation: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
authors.forename: Dong-Mei
authors.initials: DM
authors.lastname: Pu
authors.affiliation: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
authors.forename: Da-Qi
authors.initials: DQ
authors.lastname: Gao
authors.affiliation: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
authors.forename: Yu-Bo
authors.initials: YB
authors.lastname: Yuan
mesh_terms: D000465:Algorithms; D001921:Brain / Q000166:cytology* / Q000502:physiology*; D057225:Data Mining; D016208:Databases, Factual; D006801:Humans; D008954:Models, Biological; D009474:Neurons / Q000502:physiology*