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Towards robust cellular image classification: theoretical foundations for wide-angle ?scattering pattern analysis

机译:迈向鲁棒的细胞图像分类:广角散射图案分析的理论基础

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Clinical analysis of light scattering from cellular organelle distributions can help identify disease and predict a patient's response to treatment. This work presents a theoretical basis for the identification of important intracellular distributions from scattering patterns even in the presence of optical and structural variability, and examines how the geometry of an organelle distribution affects key properties of wide-angle (two-dimensional) scattering patterns. Specifically, this work demonstrates how organelle arrangement relates to the size and shape of intensity peaks within simulated scattering images, and how this relationship can affect cell identification when using standard image classification methods.
机译:从细胞器分布中散射光的临床分析可以帮助识别疾病并预测患者对治疗的反应。这项工作为从散射模式识别重要的细胞内分布提供了理论基础,即使存在光学和结构可变性,并研究了细胞器分布的几何形状如何影响广角(二维)散射模式的关键特性。具体来说,这项工作演示了细胞器排列如何与模拟散射图像中强度峰的大小和形状相关,以及当使用标准图像分类方法时这种关系如何影响细胞识别。

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