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从显微镜图像到细胞过程模型

From Microscopy Images to Models of Cellular Processes
课程网址: http://videolectures.net/ecmlpkdd08_freund_mymcp/  
主讲教师: Yoav Freund
开课单位: 加州大学圣地亚哥分校
开课时间: 2010-03-29
课程语种: 英语
中文简介:
荧光标记和共聚焦显微镜的进步使生物学家能够以几年前难以想象的细节水平来描绘生物化学过程。然而,由于这些图像的分析大多是手工完成的,因此将这些图像转换成可用于评估数学模型的有用的定量数据存在严重的瓶颈。自动化这一转换所涉及的一个固有挑战是图像数据是高度可变的。这需要重新校准每个实验的图像处理算法。我们使用机器学习方法来让实验人员在不了解这些方法如何工作的情况下校准图像处理方法。我们相信,这将使计算机视觉方法与共聚焦显微镜快速融合,为细胞过程的定量空间模型的发展开辟道路。
课程简介: The advance of fluorescent tagging and of confocal microscopy is allowing biologists to image biochemical processes at a level of detail that was unimaginable just a few years ago. However, as the analysis of these images is done mostly by hand, there is a severe bottleneck in transforming these images into useful quantitative data that can be used to evaluate mathematical models. One of the inherent challenges involved in automating this transformation is that image data is highly variable. This requires a recalibration of the image processing algorithms for each experiment. We use machine learning methods to enable the experimentalist to calibrate the image processing methods without having any knowledge of how these methods work. This, we believe, will allow the rapid integration of computer vision methods with confocal microscopy and open the way to the development of quantitative spatial models of cellular processes. 
关 键 词: 荧光标记; 共聚焦显微镜; 图像处理算法
课程来源: 视频讲座网
最后编审: 2021-02-03:nkq
阅读次数: 40