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Model-based segmentation and quantification of fluorescent bacteria in 3D microscopy live cell images

机译:基于模型的3D显微镜活细胞图像中荧光细菌的分割和定量

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摘要

We introduce a new model-based approach for segmenting and quantifying fluorescent bacteria in 3D microscopy live cell images. The approach is based on a new 3D superellipsoidal parametric intensity model, which is directly fitted to the image intensities within 3D regions-of-interest. Based on the fitting results, we can directly compute the total amount of intensity (fluorescence) of each cell. In addition, we introduce a method for automatic initialization of the model parameters, and we propose a method for simultaneously fitting clustered cells by using a superposition of 3D superellipsoids for model fitting. We demonstrate the applicability of our approach based on 3D synthetic and real 3D microscopy images.
机译:我们引入了一种基于模型的新方法,用于在3D显微镜活细胞图像中分割和量化荧光细菌。该方法基于新的3D超椭圆体参数强度模型,该模型直接适合3D感兴趣区域内的图像强度。根据拟合结果,我们可以直接计算每个细胞的强度(荧光)总量。此外,我们介绍了一种自动初始化模型参数的方法,并提出了一种通过使用3D超椭球体的叠加进行模型拟合来同时拟合聚类单元的方法。我们展示了基于3D合成和真实3D显微镜图像的方法的适用性。

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