• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Image segmentation and paired shapes asymmetry quantification: An application in a Drosophila wing image set
【24h】

Image segmentation and paired shapes asymmetry quantification: An application in a Drosophila wing image set

机译：图像分割和成对的形状不对称量化：在果蝇翅膀图像集中的应用

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The current process to identify wing pair shape asymmetry in Drosophila wing images contains multiple layers of potential measurement error. The image segmentation routine is a low-level method performed on a low resolution image set, and is prone to inaccurate edge detection in finding the wing's interior vascular structure and the exterior wing edge. An automated splining procedure on the segmentation result which yields the locations of several landmark points on the wing itself has several erroneous spline control points. The process to correct errors in the data requires both parameter tuning in the algorithm as well as manual correction of the segmentation and splining results. The in-production measures of asymmetry between Drosophila wing pairs are shown to be sensitive to these measurement errors. To reduce error in the segmentation step, several image segmentation methods are analyzed for use in developing a robust, efficient and automated segmentation algorithm for Drosophila wing image sets. Evaluation of the accuracy and efficiency of the methods is discussed, with a focus on the performance of multi-scale methods. A Frangi multi-scale segmentation is shown to more accurately locate the wing's interior vascular network. Additionally, an alternative principal components analysis of the variance structure in the image set is developed to isolate and quantify wing pair shape variation across the data set. This analysis replaces the splining process to identify locations of landmark points. Alternative measures of wing pair shape asymmetry are created from this analysis and an alternative measure of Directional Asymmetry (DA) is shown to reproduce existing benchmark measures of DA.
机译：在果蝇机翼图像中识别机翼对形状不对称的当前过程包含多层潜在的测量误差。图像分割例程是对低分辨率图像集执行的低级方法，在查找机翼的内部血管结构和外机翼边缘时，容易出现边缘检测不准确的情况。分割结果上的自动样条程序会在机翼本身上产生几个界标点的位置，因此会产生几个错误的样条控制点。校正数据错误的过程既需要算法中的参数调整，也需要对分段和样条结果进行手动校正。果蝇翅膀对之间的不对称生产量度显示对这些测量误差敏感。为了减少分割步骤中的错误，分析了几种图像分割方法，以用于开发用于果蝇翅膀图像集的鲁棒，高效和自动分割算法。讨论了方法的准确性和效率评估，重点是多尺度方法的性能。显示了Frangi多尺度分割，可以更准确地定位机翼的内部血管网络。另外，开发了图像集中方差结构的替代主成分分析，以隔离和量化整个数据集中的机翼对形状变化。该分析替代了样条过程以标识界标点的位置。通过该分析创建了机翼对形状不对称性的替代度量，并显示了方向性不对称（DA）的替代度量来重现DA的现有基准度量。

著录项

  • 作者

    Young, Gregory D.;

  • 作者单位

    California State University, Long Beach.;

  • 授予单位 California State University, Long Beach.;
  • 学科 Applied mathematics.;Biology.
  • 学位 M.S.
  • 年度 2015
  • 页码 81 p.
  • 总页数 81
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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