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Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking

机译:多级空时聚合用于明场细胞显微镜分割和跟踪

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摘要

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant “saliency measure” is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments (“object tunnels”) that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.
机译:一种多级聚合方法应用于分割活细胞明场显微镜图像的问题。所使用的方法是所谓的“通过加权聚合进行分段”技术的变体,该技术本身基于代数多重网格方法。详细描述了所使用方法的变体,并说明了如何针对当前应用进行定制。特别是,提出了一种新的尺度不变的“显着性度量”,用于确定像素集合何时构成不应进一步分组的显着片段。结果表明,仅基于多级强度相似性的分割如何无法为明场细胞带来令人满意的结果。但是,将多级强度方差(作为纹理的度量)添加到每个聚合的特征向量中会导致正确的细胞分割。提出了将时空多级聚合算法应用于显微镜图像的时间序列的初步结果,目的是获得跟踪单个细胞的时空片段(“对象隧道”)。介绍了用于在明场显微镜图像序列中对活细胞进行分割和跟踪的时空聚集方法的优缺点,并讨论了如何在将来的工作中将该方法用作一个完整的构建模块强大的细分和跟踪系统。

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