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Precise Segmentation of Nuclei in Hepatic Histological Images

机译:肝组织学图像中细胞核的精确分割

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Nuclear morphometric features such as shape of nuclei are useful in diagnosing hepatocellular carcinoma, especially well-differentiated hepatocellular carcinoma (ewHCC). We previously developed a support system for diagnosing ewHCC that enables the user to estimate the nuclear density and the roundness factor of nuclei. In the system, the contours of a nucleus are extracted as a collection of discrete contour points which are converted to a spline curve by interpolating them. The user can correct wrong contours by moving the contour points using a mouse. So, the number of contour points is limited to a small number, usually eight, in order to reduce the time for contour correction. As a result, it was difficult to precisely express the shape of nuclear contours especially in deformed nuclei. In order to solve this problem, new process to improve the contours was introduced. After the contour correction using the GUI, the contours were improved using 80 contour points. An energy function including four energy terms, the energies of the image, the distance between contour points, the curvature, and the color differences, was used. Experimental results showed this process is effective for all the three types of contours, normal round-shaped, deformed, and vague contours. The average absolute error of contour positions was reduced to about 1/3 of the conventional error. As a result, the average absolute error of nuclear areas was reduced to about 1/10, which corresponds to 0.50% of the average nuclear area. The error of roundness factors was also improved. This new process is totally automatic, which means no additional manpower is required.
机译:核形态特征如核形状,可用于诊断肝细胞癌,特别是良好分化的肝细胞癌(EWHCC)。我们之前开发了一种用于诊断EWHCC的支持系统,使用户能够估计核密度和核的圆度因子。在系统中,核的轮廓被提取为通过插值将其转换为样条曲线的分立轮廓点的集合。用户可以通过使用鼠标移动轮廓点来纠正错误的轮廓。因此,轮廓点的数量仅限于较小的数量,通常是八个,以减少轮廓校正的时间。结果,难以精确地表达核轮廓的形状,特别是在变形的核中。为了解决这个问题,介绍了改善轮廓的新进程。在使用GUI的轮廓校正之后,使用80轮廓点改善轮廓。使用包括四个能量术语的能量功能,使用图像的能量,轮廓点之间的距离,曲率与颜色差异之间的距离。实验结果表明,该过程对所有三种类型的轮廓,正常的圆形,变形和模糊轮廓有效。轮廓位置的平均绝对误差减少到传统误差的约1/3。结果,核区域的平均绝对误差减少到约1/10,其对应于平均核区域的0.50%。圆度因子的错误也得到了改善。这个新的过程是完全自动的,这意味着不需要额外的人力。

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