超分辨光学波动显微成像技术研究
发布时间：2018-10-21 09:38
【摘要】：超分辨荧光波动显微技术(Super-resolution Optical Fluctuation Imaging,SOFI)以荧光波动统计分析为基础,获取超分辨图像。通过拍摄一段连续的图像序列,使用累积算法对荧光波动进行统计分析,分析比较图像序列在这段时间内每个像素点的荧光强度闪烁情况,根据阶数不同,得到不同程度的超分辨图像,具有成像速度较快、信噪比较高、光毒性较小、系统复杂度较低等优点,可长时间观测活体生物样本,同时实现多个荧光分子高速成像。通过此课题研究的展开,可以提高SOFI成像的实时性,扩展其应用范围,也为将来仪器的研发提供理论指导。本文在对SOFI技术调研的基础上,分别从SOFI成像原理,图像重构算法及实验装置三个方面对超分辨光学波动显微成像技术进行了深入的研究。主要研究内容为:(1)对SOFI成像理论深入研究,结合SOFI成像条件,分析SOFI图像重构算法原理、样本的光学特性和有效像元尺寸对图像的影响。(2)研究了两种提高SOFI图像空间分辨率的图像重构算法,高阶SOFI算法和傅里叶SOFI算法。对仿真数据进行验证,分析两种算法的优缺点及局限性。(3)为了提高SOFI算法的实时性,提出基于空间disk滤波的SOFI算法。对获取的多帧图像先进行滤波处理,再根据多帧图像中荧光粒子的时间自相关性进行SOFI算法处理,可快速得到高信噪比的超分辨图像。通过数据分析验证了基于空间高斯disk滤波的SOFI算法可以在低信噪比的图像序列中快速得到信噪比较高的超分辨图像。(4)基于倒置荧光显微镜,搭建SOFI系统成像光路,采用汞灯作为激发光,使用商用荧光量子点QDot525作为样本,利用sCMOS相机记录宽场显微图像。对实验结果进行分析找到最佳的图像帧数、曝光时间、有效像元尺寸。结合本文提出的算法和SOFI图像的影响因素,达到能够在最短时间内得到最优的超分辨图像的目的。
[Abstract]:Super-resolution fluorescence wave microscopy (Super-resolution Optical Fluctuation Imaging,SOFI) is based on statistical analysis of fluorescence fluctuations to obtain super-resolution images. By taking a continuous sequence of images and using the cumulative algorithm to analyze the fluorescence fluctuation, the fluorescence intensity flicker of each pixel in the image sequence during this period is analyzed and compared. According to the different order, the fluorescence intensity flicker of each pixel in the image sequence is analyzed and compared. The super-resolution images with different degrees have the advantages of high imaging speed, high signal-to-noise ratio, low phototoxicity and low system complexity. It can be used to observe living biological samples for a long time and to realize high speed imaging of several fluorescent molecules at the same time. Through the development of this research, the real-time of SOFI imaging can be improved, its application scope can be expanded, and the theoretical guidance for the future research and development of the instrument can also be provided. Based on the investigation of SOFI technology, the super-resolution optical wave microscopic imaging technology is studied from three aspects: the principle of SOFI imaging, the image reconstruction algorithm and the experimental device. The main contents are as follows: (1) the theory of SOFI imaging is deeply studied, and the principle of SOFI image reconstruction algorithm is analyzed according to the conditions of SOFI imaging. The influence of the optical properties of the sample and the size of the effective pixel on the image. (2) two image reconstruction algorithms, high-order SOFI algorithm and Fourier SOFI algorithm, are studied to improve the spatial resolution of SOFI images. The simulation data are verified and the advantages and disadvantages of the two algorithms are analyzed. (3) in order to improve the real-time performance of the SOFI algorithm, a SOFI algorithm based on spatial disk filtering is proposed. The acquired multi-frame images are filtered first and then processed by SOFI algorithm according to the time autocorrelation of fluorescent particles in multi-frame images. The super-resolution images with high signal-to-noise ratio can be obtained quickly. The data analysis shows that the SOFI algorithm based on spatial Gao Si disk filter can quickly obtain super-resolution images with high SNR in low SNR image sequences. (4) based on inverted fluorescence microscope, the imaging optical path of SOFI system is built. Mercury lamp was used as excitation light and commercial fluorescent quantum dot (QDot525) was used as sample. Wide field microscopic images were recorded by sCMOS camera. The experimental results are analyzed to find the best image frame number, exposure time and effective pixel size. Combined with the algorithm presented in this paper and the influencing factors of SOFI images, the optimal super-resolution image can be obtained in the shortest time.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP391.41
本文编号：2284716
[Abstract]:Super-resolution fluorescence wave microscopy (Super-resolution Optical Fluctuation Imaging,SOFI) is based on statistical analysis of fluorescence fluctuations to obtain super-resolution images. By taking a continuous sequence of images and using the cumulative algorithm to analyze the fluorescence fluctuation, the fluorescence intensity flicker of each pixel in the image sequence during this period is analyzed and compared. According to the different order, the fluorescence intensity flicker of each pixel in the image sequence is analyzed and compared. The super-resolution images with different degrees have the advantages of high imaging speed, high signal-to-noise ratio, low phototoxicity and low system complexity. It can be used to observe living biological samples for a long time and to realize high speed imaging of several fluorescent molecules at the same time. Through the development of this research, the real-time of SOFI imaging can be improved, its application scope can be expanded, and the theoretical guidance for the future research and development of the instrument can also be provided. Based on the investigation of SOFI technology, the super-resolution optical wave microscopic imaging technology is studied from three aspects: the principle of SOFI imaging, the image reconstruction algorithm and the experimental device. The main contents are as follows: (1) the theory of SOFI imaging is deeply studied, and the principle of SOFI image reconstruction algorithm is analyzed according to the conditions of SOFI imaging. The influence of the optical properties of the sample and the size of the effective pixel on the image. (2) two image reconstruction algorithms, high-order SOFI algorithm and Fourier SOFI algorithm, are studied to improve the spatial resolution of SOFI images. The simulation data are verified and the advantages and disadvantages of the two algorithms are analyzed. (3) in order to improve the real-time performance of the SOFI algorithm, a SOFI algorithm based on spatial disk filtering is proposed. The acquired multi-frame images are filtered first and then processed by SOFI algorithm according to the time autocorrelation of fluorescent particles in multi-frame images. The super-resolution images with high signal-to-noise ratio can be obtained quickly. The data analysis shows that the SOFI algorithm based on spatial Gao Si disk filter can quickly obtain super-resolution images with high SNR in low SNR image sequences. (4) based on inverted fluorescence microscope, the imaging optical path of SOFI system is built. Mercury lamp was used as excitation light and commercial fluorescent quantum dot (QDot525) was used as sample. Wide field microscopic images were recorded by sCMOS camera. The experimental results are analyzed to find the best image frame number, exposure time and effective pixel size. Combined with the algorithm presented in this paper and the influencing factors of SOFI images, the optimal super-resolution image can be obtained in the shortest time.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP391.41
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