首页> 外文会议>International symposium on mathematical morphology >Hourglass Shapes in Rank Grey-Level Hit-or-miss Transform for Membrane Segmentation in HER2eu Images
【24h】

Hourglass Shapes in Rank Grey-Level Hit-or-miss Transform for Membrane Segmentation in HER2eu Images

机译:HER2 / neu图像中用于膜分割的等级灰度命中或缺失变换中的沙漏形状

获取原文

摘要

The paper presents an automatic approach to the analysis of images of breast cancer tissue stained with HER2 antibody. It applies the advanced morphological tools to build the system for recognition of the cell nuclei and the membrane localizations. The final results of image processing is the computerized method of estimation of the membrane staining continuity. The important point in this approach is application of the hourglass shapes in rank grey-level hit-or-miss transform of the image. The experimental results performed on IS cases have shown high accuracy of the nuclei and membrane localizations. The mean absolute error of continuity estimation of the stained membrane between the expert and our system results was 6.1% at standard deviation of 3.2%. These results confirm high efficiency of the proposed solution.
机译:本文提出了一种自动方法来分析被HER2抗体染色的乳腺癌组织的图像。它使用先进的形态学工具来构建用于识别细胞核和膜定位的系统。图像处理的最终结果是估计膜染色连续性的计算机化方法。这种方法的重点是在图像的灰度灰度级命中或遗漏变换中应用沙漏形状。在IS病例上进行的实验结果表明核和膜定位的准确性很高。专家和我们的系统结果之间的连续连续估计污迹膜的平均绝对误差为6.1%,标准偏差为3.2%。这些结果证实了所提出解决方案的高效率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号