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首页> 外文期刊>Medical image analysis >Cell segmentation in phase contrast microscopy images via semi-supervised classification over optics-related features
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Cell segmentation in phase contrast microscopy images via semi-supervised classification over optics-related features

机译：通过光学相关特征的半监督分类在相衬显微镜图像中进行细胞分割

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摘要

Phase-contrast microscopy is one of the most common and convenient imaging modalities to observe long-term multi-cellular processes, which generates images by the interference of lights passing through transparent specimens and background medium with different retarded phases. Despite many years of study, computer-aided phase contrast microscopy analysis on cell behavior is challenged by image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose (1) a phase contrast microscopy image restoration method that produces phase retardation features, which are intrinsic features of phase contrast microscopy, and (2) a semi-supervised learning based algorithm for cell segmentation, which is a fundamental task for various cell behavior analysis. Specifically, the image formation process of phase contrast microscopy images is first computationally modeled with a dictionary of diffraction patterns; as a result, each pixel of a phase contrast microscopy image is represented by a linear combination of the bases, which we call phase retardation features. Images are then partitioned into phase-homogeneous atoms by clustering neighboring pixels with similar phase retardation features. Consequently, cell segmentation is performed via a semi-supervised classification technique over the phase-homogeneous atoms. Experiments demonstrate that the proposed approach produces quality segmentation of individual cells and outperforms previous approaches.
机译：相差显微镜是观察长期多细胞过程的最常见，最方便的成像方式之一，该过程通过光线穿过透明标本和具有不同延迟相位的背景介质的干扰来生成图像。尽管进行了多年的研究，但计算机辅助的相差显微镜对细胞行为的分析仍受到相差光学器件引起的图像质量和伪影的挑战。针对尚未解决的挑战，作者提出（1）一种相衬显微镜图像恢复方法，该方法可产生相延迟特征，这是相衬显微镜的固有特征;（2）一种基于半监督学习的细胞分割算法，即各种细胞行为分析的基本任务。具体而言，首先用衍射图字典对相差显微镜图像的成像过程进行建模。结果，相衬显微镜图像的每个像素都由碱基的线性组合表示，我们称其为相位延迟特征。然后，通过对具有相似相位延迟特征的相邻像素进行聚类，将图像划分为同相原子。因此，通过半监督分类技术对相均质原子进行细胞分割。实验表明，所提出的方法可以对单个细胞进行质量分割，并且优于以前的方法。

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