%0 Journal Article
%T Gouraud Shading to Improve Appearance of Neuronal Morphology Visualization
%A Norhasana Razzali
%A Mohd Shafry Mohd Rahim
%A Rosely Kumoi
%A Daut Daman
%J International Journal of Biometric and Bioinformatics
%D 2010
%I Computer Science Journals
%X This study is focused on Gouraud Shading¡¯s approach to improve appearance ofneuron visualization. Neuron visualization is a computational tool that is able todescribe, generate, store and render large set of three-dimensional neuronalmorphology in a format that is compact, quantitative, and readily accessible tothe neuroscientists. This tool enlightens its ability as a powerful computationalmodeling of neuronal morphology to explore greater understanding in neurondevelopmental processes and structure-function relationships. However, after athorough investigation, one of the problems discovered in neuron structureprediction is related to misleading in generating digitalized neuron raw datatoward realistic neuron morphology visualization. For that reason, manyapproaches have been proposed in previous studies in order to perform suchvisualization based on stochastic sampling data of morphological measures fromdigital reconstructions of real neuron cells. Therefore, comparison among theseapproaches has been conducted to recognize a suitable approach. It is still at apreliminary stage in research development. This exercise reveals a constraint to reconstruct neuron model towards greater realism efficiently is still remains as anessential challenge in biological computing and visualization to provide a broadappearance of neuron knowledge distribution. As a result, the areas ofcomparative neuron analysis can be aided through presenting the knowledge ofrealism virtual neuron morphology. As a proposal, Gouraud Shading¡¯s approachis applied for this purpose. Gouraud Shading is a visualization shading techniqueto perform a smooth lighting on the polygon surface without heavy computationalrequirement in calculating lighting for each pixel but at vertices only. Theconclusion is summarized based on verification exercise between ourframework¡¯s results with existing results from three neuron visualizationapplications. The comparison analysis is done in term of reliability andsmoothness of surface neuron presentation. Roughly the proposed frameworkachieved the objective to solve the problem encountered in presenting virtualneuron data.
%K Neuron morphology data
%K visualization
%K Gouraud Shading
%U http://www.cscjournals.org/csc/manuscript/Journals/IJBB/volume4/Issue2/IJBB-57.pdf