基于像散的三维超分辨定位显微成像技术及过程优化
[Abstract]:Since the birth of super-resolution positioning microscopy imaging technology has been widely used in the field of biology because of its ultra-high spatial resolution which breaks the diffraction limit and the simplicity of the system. Because the research of life science in nanometer scale usually requires three-dimensional spatial information, 3D super-resolution localization microscopic imaging method emerges as the times require. In the present method of 3D super-resolution positioning and microscopic imaging, the optical astigmatic method is popular because of its simplicity and good effect, but there is a lack of quantitative analysis of the performance of the method. Therefore, it can not provide an effective imaging optimization scheme for the experimental process of biological problem dependence. In order to overcome the above difficulties, through the quantitative analysis and comparison of the 3D imaging system and the image processing methods after acquisition, an optimized experimental scheme is provided, and the better imaging depth and positioning accuracy are obtained. It provides a valuable reference for the system construction and image processing of three-dimensional super-resolution micro imaging. The main work of this paper is as follows: (1) Optimization of three-dimensional super-resolution positioning micro imaging system. The influence of the position of the cylindrical mirror and focal length parameters on the point diffusion function in the astigmatic 3D imaging system is analyzed, and the cylindrical mirror parameters when the point diffusion function is optimal are obtained. (2) the image processing method is optimized. Firstly, we compare different original image preprocessing methods and obtain the optimal image preprocessing method for 3D super-resolution data. Secondly, we compare the localization effect of different single molecular localization algorithms in astigmatic 3D imaging. The optimal single molecule localization algorithm in the specific imaging depth range is obtained. Finally, a 3D data processing method based on GPU parallel computing architecture is preliminarily designed and implemented. The data processing speed of the whole data analysis process is optimized. (3) through simulation and fluorescence ball model experiment, the effect of the optimized implementation based on this system is verified. The three dimensional superresolution localization microscopic imaging results based on this system are obtained by cell microtubule imaging and brain slice imaging. The experimental results show that the optimized scheme can achieve deeper imaging depth and higher positioning accuracy.
【学位授予单位】:华中科技大学
【学位级别】:硕士
【学位授予年份】:2016
【分类号】:TP391.41
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