Three-dimensional tracking of GLUT4 vesicles in TIRF microscopy  

作　　者：Xiang-ping WU Jie-yue LI Ying-ke XU Ke-di XU Xiao-xiang ZHENG 

机构地区：[1]Department of Biomedical Engmeermg, Zhejiang University, Hangzhou 310027, China [2]College of Information Engineering, China Jiliang University, Hangzhou 310018, China

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2008年第2期232-240,共9页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：Project supported by the National Natural Science Foundation ofChina (No. 30770596);the Key Laboratory for Biomedical En-gineering of Ministry of Education of China

摘　　要：TIRF microscopy has provided a means to view mobile granules within 100 nm in size in two dimensions.However quantitative analysis of the position and motion of those granules requires an appropriate tracking method.In this paper,we present a new tracking algorithm combined with the unique features of TIRF.Firstly a fluorescence correction procedure was processed to solve the problem of fluorescence bleaching over time.Mobile granules were then segmented from a time-lapse image stack by an adaptive background subtraction method.Kalman filter was introduced to estimate and track the granules that allowed reducing searching range and hence greater reliability in tracking process.After the tracked granules were located in x-y plane,the z-position was indirectly inferred from the changes in their intensities.In the experiments the algorithm was applied in tracking GLUT4 vesicles in living adipose cells.The results indicate that the algorithm has achieved robust estimation and tracking of the vesicles in three dimensions.TIRF microscopy has provided a means to view mobile granules within 100 nm in size in two dimensions. However quantitative analysis of the position and motion of those granules requires an appropriate tracking method. In this paper, we present a new tracking algorithm combined with the unique features of TIRF. Firstly a fluorescence correction procedure was processed to solve the problem of fluorescence bleaching over time. Mobile granules were then segmented from a time-lapse image stack by an adaptive background subtraction method. Kalman filter was introduced to estimate and track the granules that allowed reducing searching range and hence greater reliability in tracking process. After the tracked granules were located in x-y plane, the z-position was indirectly inferred from the changes in their intensities. In the experiments the algorithm was applied in tracking GLUT4 vesicles in living adipose cells. The results indicate that the algorithm has achieved robust estimation and tracking of the vesicles in three dimensions.

关 键 词：GLUT4 Total internal reflection fluorescence （TIRF） microscopy Adaptive background subtraction Kalman filter Fluorescence correction 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论] Q27[自动化与计算机技术—计算机科学与技术]