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Touching Soma Segmentation Based on the Rayburst Sampling Algorithm

机译：基于雷根斯法采样算法触摸SOMA分割

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摘要

Neuronal soma segmentation is essential for morphology quantification analysis. Rapid advances in light microscope imaging techniques have generated such massive amounts of data that time-consuming manual methods cannot meet requirements for high throughput. However, touching soma segmentation is still a challenge for automatic segmentation methods. In this paper, we propose a soma segmentation method that combines the Rayburst sampling algorithm and ellipsoid fitting. The improved Rayburst sampling algorithm is used to detect the soma surface; the ellipsoid fitting method then refines jagged sampled soma surface to generate smooth ellipsoidal shapes for efficient analysis. In experiments, we validated the proposed method by applying it to datasets from the fluorescence micro-optical sectioning tomography (fMOST) system. The results indicate that the proposed method is comparable to the manual segmented gold standard with accurate soma segmentation at a relatively high speed. The proposed method can be extended to large-scale image stacks in the future.
机译：神经元SOMA分割对于形态学定量分析至关重要。光学显微镜成像技术的快速进步已经产生了耗时的手动方法不能满足高吞吐量要求的大量数据。但是，触摸SOMA分段仍然是自动分段方法的挑战。在本文中，我们提出了一种SOMA分段方法，结合了雷爆采样算法和椭圆形配件。改进的Rayburst采样算法用于检测SOMA表面;然后，椭球配合方法细化锯齿状取样躯体表面以产生平滑的椭圆形形状以进行有效分析。在实验中，我们通过将其应用于来自荧光微光学切片断层扫描（最小）系统的数据集来验证了所提出的方法。结果表明，该方法与手动分段的金标准相当，具有较高的速度精确的SOMA分段。所提出的方法可以在将来扩展到大规模的图像堆栈。

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  • 来源
    《Neuroinformatics》 |2017年第4期|共11页
  • 作者

    Hu Tianyu; Xu Qiufeng; Lv Wei; Liu Qian;

  • 作者单位

    Huazhong Univ Sci &

    Technol Sch Engn Sci Britton Chance Ctr Biomed Photon Wuhan Natl Lab Optoelect Huazhong Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol Sch Engn Sci Britton Chance Ctr Biomed Photon Wuhan Natl Lab Optoelect Huazhong Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol Sch Engn Sci Britton Chance Ctr Biomed Photon Wuhan Natl Lab Optoelect Huazhong Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol Sch Engn Sci Britton Chance Ctr Biomed Photon Wuhan Natl Lab Optoelect Huazhong Wuhan 430074 Hubei Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工神经网络与计算;
  • 关键词

    Image analysis; Soma segmentation; Rayburst sampling algorithm; Distance transform;

    机译：图像分析;SOMA分割;Rayburst采样算法;距离变换;

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