Smal Ihor, Draegestein Katharina, Galjart Niels, Niessen Wiro, Meijering Erik
Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center Rotterdam, The Netherlands.
Inf Process Med Imaging. 2007;20:110-21. doi: 10.1007/978-3-540-73273-0_10.
Modern live cell fluorescence microscopy imaging systems, used abundantly for studying intra-cellular processes in vivo, generate vast amounts of noisy image data that cannot be processed efficiently and accurately by means of manual or current computerized techniques. We propose an improved tracking method, built within a Bayesian probabilistic framework, which better exploits temporal information and prior knowledge. Experiments on simulated and real fluorescence microscopy image data acquired for microtubule dynamics studies show that the technique is more robust to noise, photobleaching, and object interaction than common tracking methods and yields results that are in good agreement with expert cell biologists.
现代活细胞荧光显微镜成像系统被大量用于体内细胞内过程的研究，它会生成大量有噪声的图像数据，而这些数据无法通过手动或当前的计算机技术进行高效且准确的处理。我们提出了一种改进的跟踪方法，该方法构建在贝叶斯概率框架内，能更好地利用时间信息和先验知识。对为微管动力学研究获取的模拟和真实荧光显微镜图像数据进行的实验表明，与常见的跟踪方法相比，该技术对噪声、光漂白和物体相互作用具有更强的鲁棒性，并且产生的结果与细胞生物学专家的结果高度一致。
