【摘要】 高通量荧光显微图像数据定量分析,是研究活细胞动态过程的有力工具。亚细胞观察对象在图像中常以衍射极限点斑的形式出现。成像条件的限制往往导致荧光显微图像均一度差、信噪比较低,给人工分析带来了挑战。设计自动化的亚细胞斑点检测方法,是高通量荧光显微图像数据处理的必要前提。本文就近年来斑点检测的关键技术进行了较详尽的综述,包括降噪滤波、信号增强和信号阈值化。在总结现有斑点检测方法优缺点的基础上,讨论算法设计的瓶颈和共性难点,并对相关研究做了展望。更多还原

【Abstract】 Quantitative analysis of high throughput fluorescence microscopic image is a powerful tool to study dynamic processes in living cells.Many subcellular objects of interest appear as diffraction-limited spots in the image.The limitations of imaging conditions often lead to fluorescence microscopic images inhomogeneous and lower signal-to-noise ratio(SNR),making manual analysis a very challenging task.Designing the automatic subcellular spot detection method is a prerequisite for high throughput fluorescence microscopic image processing.This review presented a detailed overview of recent advances in the key techniques of spot detection method,including noise reduction,signal enhancement and signal thresholding.The bottlenecks and common difficulties of the algorithm design were discussed on the basis of summarizing advantages and disadvantages of the exiting spot detection methods.At the same time,the prospect of the related research was discussed.更多还原