Beer's Law explains how light attenuates into thick specimens, including thick biofilms. We use a Bayesian optimality criterion, the maximum of the posterior probability distribution, and computationally efficiently fit Beer's Law to the 3D intensity data collected from thick living biofilms by a confocal scanning laser microscope. Using this approach the top surface of the biofilm and an optimal image threshold can be estimated. Biofilm characteristics, such as bio-volumes, can be calculated from this surface. Results from the Bayesian approach are compared to other approaches including the method of maximum likelihood or simply counting bright pixels. Uncertainty quantification (i.e., error bars) can be provided for the parameters of interest. This approach is applied to confocal images of stained biofilms of a common lab strain of Pseudomonas aeruginosa, stained biofilms of Janthinobacterium isolated from the Antarctic, and biofilms of Staph aureus that have been genetically modified to fluoresce green.

中文翻译：

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使用比尔定律对生物膜的共聚焦显微镜图像进行最佳表面估计和阈值处理。

比尔定律解释了光如何衰减成厚厚的样本，包括厚厚的生物膜。我们使用贝叶斯最优性准则，后验概率分布的最大值，并通过共聚焦扫描激光显微镜有效地将比尔定律与从厚的生物膜上采集的3D强度数据进行计算拟合。使用这种方法，可以估计生物膜的顶表面和最佳图像阈值。可以从该表面计算生物膜特征，例如生物体积。贝叶斯方法的结果与其他方法进行了比较，包括最大似然法或仅对明亮像素进行计数。可以为感兴趣的参数提供不确定性量化（即误差条）。