.3 D Fluorescent Confocal Image The Extracted Detection Algorithm Of The Neural Dendritic Spines,

The research of dendrite and spines is important in neurobiology, and brain's function is closely related to neuronal morphology and structure. We can understand how the brain work, theory of memory and prevent some neurological diseases by study neuron. Dendrite are the branched projections of a neuron that act to conduct the electrochemical stimulation received from other neural cells to the cell body, spines are protrusions attached to the surface of the dendrite, which transmitting electrochemical stimulation between different dendrites. Changes of the shape of spines in certain brain areas reflect the learning processes. it's very complicated for us to using manual identification deal with 3D fluorescence confocal microscopy image sample. and extraction accuracy is difficult to meet the requirements. so we need to study computer automated extraction and detection methods. this paper focuses on 3D dendrites extracted and spines detection, proposed a systemic solution.main work:(1) Designing a 3D confocal image segmentation method based on BM3D and level set. Experimental results show that it's accurate to dendrites segmentation.(2) Designing a seed point detection algorithm based on generalized gradient vector field, calculate critical points and high curvature points depend on GGVF.(3) We use tree model describing dendrite and spines through minimun spanning tree, proposed a center line extracted method based on figure cut and erosion. We use B-spline fitting to improve smoothness of the skeleton.(4) Designing a spines detected algorithm based on LDA.(5) Droposed an automatic 3D confocal image of dendrite segmented and spine detected program based on the above process. Experiments show its effectiveness.