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AUTOMATIC METHOD FOR CAVEOLAR STRUCTURE DETECTION AND INTENSITY DISTRIBUTION ANALYSIS FROM MICROSCOPY IMAGES

机译:来自显微镜图像的Caveolar结构检测和强度分布分析的自动化方法

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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:Caveolin的荧光融合蛋白寡聚化形成血浆膜凹坑,称为Caveolae。可以通过显微镜图像中坑的荧光强度估计凹坑中的Caveolin蛋白的量。在本研究中,引入了一种自动方法,用于凹坑识别,强度测量和强度分布参数估计。点被识别并与非Caveolar结构分离。用新的自动方法测量强度,该方法能够估计来自所有识别的凹坑的强度。从异常值清理强度分布,并用正常分布的混合模型建模。用遗传算法自动搜索最佳参数集混合模型。

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