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基于图的视网膜镶嵌和血管特征分析方法

Graph-based Methods for Retinal Mosaicing and Vascular Characterization
课程网址: http://videolectures.net/gbr07_perez_gbrmr/  
主讲教师: M. Elena Martinez-Perez
开课单位: 墨西哥国立大学
开课时间: 2007-07-04
课程语种: 英语
中文简介:
在本文中,我们提出了一种高度鲁棒的点匹配方法(图形转换匹配GTM),它依赖于从推定匹配中找到共识图。这种方法是两阶段的,在找到共识图之后,它试图尽可能地完成它。我们成功地将GTM应用于从视网膜图像中找到马赛克的背景下的图像配准。在正确分割这些图像之后获得特征点。此外,我们还引入了一种新的拓扑描述符,用于通过表征动脉/小静脉树来量化疾病。这种描述符依赖于图上的扩散核。我们的实验仅显示了动脉树的统计学意义,这与之前的研究结果一致。
课程简介: In this paper, we propose a highly robust point-matching method (Graph Transformation Matching - GTM) relying on finding the consensus graph emerging from putative matches. Such method is a two- phased one in the sense that after finding the consensus graph it tries to complete it as much as possible. We successfully apply GTM to image registration in the context of finding mosaics from retinal images. Feature points are obtained after properly segmenting such images. In addition, we also introduce a novel topological descriptor for quantifying disease by characterizing the arterial/venular trees. Such descriptor relies on diffusion kernels on graphs. Our experiments have showed only statistical signifficance for the case of arterial trees, which is consistent with previous findings.
关 键 词: 点匹配方法; 共识图; 视网膜图像
课程来源: 视频讲座网
最后编审: 2019-04-14:cwx
阅读次数: 69