【摘要】：超分辨定位顯微成像技術(shù)自從誕生以來(lái),因具有打破衍射極限的超高空間分辨率以及系統(tǒng)簡(jiǎn)易的特點(diǎn)在生物學(xué)領(lǐng)域獲得廣泛應(yīng)用。由于在納米尺度進(jìn)行生命科學(xué)問題的研究通常需要立體三維的空間信息,三維超分辨定位顯微成像方法應(yīng)運(yùn)而生。在目前實(shí)現(xiàn)三維超分辨定位顯微成像的方法中,基于光學(xué)像散實(shí)現(xiàn)的方法由于實(shí)現(xiàn)簡(jiǎn)單且效果好而備受青睞,但是目前缺乏對(duì)其實(shí)現(xiàn)方法性能的定量分析,從而無(wú)法為生物問題依賴的實(shí)驗(yàn)過程提供有效的成像優(yōu)化方案。為了克服上述困難,本論文通過對(duì)三維成像系統(tǒng)以及采集后圖像處理方法進(jìn)行全面的定量分析對(duì)比,提供了一個(gè)優(yōu)化的實(shí)驗(yàn)方案,得到了較優(yōu)的成像深度及定位精度,為三維超分辨定位顯微成像的系統(tǒng)搭建和圖像處理提供了很有價(jià)值的參考。本文的三個(gè)主要工作如下:(1)三維超分辨定位顯微成像系統(tǒng)的優(yōu)化。分析了基于像散的三維成像系統(tǒng)中關(guān)鍵器件——柱面鏡的位置及焦距參數(shù)對(duì)點(diǎn)擴(kuò)散函數(shù)的影響,得到了點(diǎn)擴(kuò)散函數(shù)最優(yōu)時(shí)的柱面鏡參數(shù)。(2)圖像處理方法的優(yōu)化。首先,分析比較不同的原始圖像預(yù)處理方法,得到對(duì)三維超分辨數(shù)據(jù)最優(yōu)的圖像預(yù)處理方法;其次比較不同的單分子定位算法在基于像散的三維成像中的定位效果,獲得在特定成像深度范圍內(nèi)最優(yōu)的單分子定位算法;最后初步設(shè)計(jì)并實(shí)現(xiàn)了基于GPU并行計(jì)算架構(gòu)的三維數(shù)據(jù)處理方法,使整個(gè)數(shù)據(jù)分析過程在數(shù)據(jù)處理速度上得到優(yōu)化。(3)通過仿真和熒光小球模型實(shí)驗(yàn)驗(yàn)證基于本系統(tǒng)優(yōu)化后的實(shí)現(xiàn)效果,并且通過細(xì)胞微管成像實(shí)驗(yàn)和腦片成像實(shí)驗(yàn)得到基于本系統(tǒng)的三維超分辨定位顯微成像結(jié)果。實(shí)驗(yàn)結(jié)果表明,優(yōu)化后的實(shí)驗(yàn)方案能夠達(dá)到更深的成像深度及更高的定位精度。
[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.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

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