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Automatic method for caveolar structure detection and intensity distribution analysis from microscopy images

机译:显微图像的海绵体结构检测和强度分布自动分析方法

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Fluorescent fusion proteins of caveolin oligomerize to form plasma membrane pits, called caveolae. Amount of caveolin protein in a pit can be estimated by fluorescence intensity of the pit in microscopy image. In this study an automatic method is introduced for pit recognition, intensity measurement and intensity distribution parameter estimation. Dots are recognised and separated from non-caveolar structures. Intensities are measured with a new automatic method, which is capable of estimating intensities from all the recognised pits. Intensity distribution is cleaned up from outliers and modelled with a mixture model of normal distributions. Optimal parameter set of mixture model is searched automatically with a genetic algorithm.
机译:小窝蛋白的荧光融合蛋白低聚形成质膜凹坑,称为小窝。凹坑中小窝蛋白的量可以通过显微镜图像中凹坑的荧光强度来估计。在这项研究中,介绍了一种自动方法,用于坑识别,强度测量和强度分布参数估计。点被识别并与非牙槽结构分开。用新的自动方法测量强度,该方法能够从所有识别出的凹坑中估计强度。从异常值中清除强度分布,并使用正态分布的混合模型建模。利用遗传算法自动搜索混合模型的最佳参数集。

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