Curve interpolation model for visualising disjointed neural elements

作     者：Mohd Shafry Mohd Rahim Norhasana Razzali Mohd Shahrizal Sunar Ayman Abdualaziz Abdullah Amjad Rehman 

作者机构：UTMViCubeLab Department of Computer Graphics and Multimedia FSKSM University of Technology College of Applied Studies and Community Service King Saud University 

出 版 物：《Neural Regeneration Research》 (中国神经再生研究（英文版）)

年 卷 期：2012年第7卷第21期

页      面：1637-1644页

核心收录：

学科分类：0710[理学-生物学] 1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 07[理学] 071006[理学-神经生物学] 

基　　金：supported by UTMVicubeLab at Department of Computer Graphics and Multimedia, Faculty of Computer Science and Information System, University Technology Malaysia Special thanks to Ministry of Science and Technology Innovation for providing financial support for this research 

主　　题：bounding cylinder curve interpolation reconstruction model Gouraud shading neuralregeneration 

摘      要：Neuron cell are built from a myriad of axon and denddte structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain＇s functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron＇s connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts＇ responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.