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首页> 外文会议>Conference on Three-dimensional and multidimensional microscopy: Image acquisition and processing >Image estimation accounting for point-spread function depth variation in three-dimensional fluorescence microscopy
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Image estimation accounting for point-spread function depth variation in three-dimensional fluorescence microscopy

机译：三维荧光显微镜中点扩展功能深度变化的图像估计算

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An approximate model for optical-sectioning microscopy describing depth-varying imaging is developed. The model incorporates changes in the point-spread function due to refractive index mismatch between the immersion medium and the specimen, which causes spherical aberration that worsens with increasing depth under the coverslip. Comparison of model predictions to measured images from a bead phantom shows that the approximate model captures the main features in the data. The model presented in this paper is the first step towards depth-variant image estimation for optical-sectioning microscopy. An expectation maximization algorithm for maximum-likelihood restoration based on this model is also presented.
机译：开发了描述深度变化成像的光学截面显微镜的近似模型。由于浸渍介质和样本之间的折射率失配，该模型包括点扩散功能的变化，这导致球形像差随着盖玻片下的深度而变得越来越多的球形像差。从珠光幻影测量图像的模型预测的比较表明近似模型捕获数据中的主要特征。本文呈现的模型是朝向光学截面显微镜进行深度变体图像估计的第一步。还介绍了基于该模型的最大似然恢复的期望最大化算法。

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