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首页> 外文会议>IEEE International Symposium on Biomedical Imaging: From Nano to Macro >A general approach for segmenting elongated and stubby biological objects: Extending a chord length transform with the Radon transform
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A general approach for segmenting elongated and stubby biological objects: Extending a chord length transform with the Radon transform

机译：分割细长的和粗短的生物对象的通用方法：使用Radon变换扩展弦长变换

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Automatic, high-throughput, quantification of the precise position and orientation of biological objects is essential for studying living, biomedically relevant processes from time-lapse microscopy images. These measurements frequently include precise estimates for the center-of-mass as well as the location of the true object boundaries e.g. the membranes of cells. This paper describes a region-oriented segmentation approach applied to the detection of both insects at the mm length scale as well as bacteria at the μm length scale. Despite the differences in length scale, images of both objects have similar aspect ratio, and it is common to have overlapping objects in images of both. This thus presents a challenge for any segmentation algorithm. Our approach performs all orientation detection through a chord length transform, so the task of separating overlapping objects in a two-dimensional image is reformulated as a voxel-labeling problem within a three-dimensional volume. It then utilizes the directional information from the Radon transformed image. Experimental results in simulation show that our method is effective in separating clustered elongated but stubby objects with aspect ratios not far from 1. The applications in detecting insects and Escherichia coli bacteria demonstrate the value of our approach.
机译：对生物对象的精确位置和方向进行自动，高通量的定量分析对于从延时显微镜图像研究生物相关的生物过程至关重要。这些测量通常包括对质量中心以及真实物体边界位置的精确估计，例如：细胞膜。本文介绍了一种面向区域的分割方法，该方法适用于检测毫米长度尺度的昆虫以及微米长度尺度的细菌。尽管长度比例有所不同，但是两个对象的图像都具有相似的宽高比，并且在两个图像中通常都有重叠的对象。因此，这对任何分割算法都提出了挑战。我们的方法通过弦长变换执行所有方向检测，因此将二维图像中的重叠对象分离的任务重新构造为三维体积内的体素标记问题。然后，它利用Radon变换图像中的方向信息。仿真实验结果表明，该方法可以有效地分离长宽比不超过1的簇状细长但粗短的物体。在检测昆虫和大肠杆菌中的应用证明了该方法的价值。

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