删除或更新信息,请邮件至freekaoyan#163.com(#换成@)

基于Hessian矩阵和熵的眼底图像血管分割

本站小编 Free考研考试/2021-12-21

本文二维码信息
二维码(扫一下试试看!)
基于Hessian矩阵和熵的眼底图像血管分割
Vessel Segmentation in Fundus Images Based on Hessian Matrix and Entropy
投稿时间:2016-11-19
DOI:10.15918/j.tbit1001-0645.2017.增刊1.030
中文关键词:血管分割眼底图像Hessian矩阵熵阈值
English Keywords:vessel segmentationfundus imagesHessian matrixentropic thresholding
基金项目:国家自然科学基金资助项目(61571070);重庆科委自然科学基金资助项目(cstc2016jcyjA0347);重庆高校创新团队建设计划(智慧医疗系统与核心技术CXTDG201602009);重庆市重点实验室能力提升项目("光电信息感测与传输技术"重庆市重点实验室cstc2014pt-sy40001);重庆市基础科学与前沿技术研究专项基金资助项目(cstc2017jcyjbx0057,cstcjcyjA0982);重庆邮电大学科研启动基金资助项目(A2016-73);重庆邮电大学文峰人才计划
作者单位E-mail
王慧倩重庆邮电大学 重庆 400065
庞宇重庆邮电大学 重庆 400065pangyu@cqupt.edu.cn
林金朝重庆邮电大学 重庆 400065
李章勇重庆邮电大学 重庆 400065
姜小明重庆邮电大学 重庆 400065
蒋宇皓重庆邮电大学 重庆 400065
摘要点击次数:726
全文下载次数:253
中文摘要:
为了实现眼底图像血管自动准确分割,研究了一种基于Hessian矩阵线状滤波和熵阈值的分割方法.采用基于Hessian矩阵的多尺度线状滤波增强血管区域,结合滤波后灰度和具有方向性的线状邻域内灰度均值建立二维直方图,再根据直方图的最大类熵确定阈值,得到血管的二值化分割结果.实验表明,相比其它两种已有方法,提出的方法能够自动地得到更完整、更准确的眼底图像血管分割结果.
English Summary:
Vessel segmentation is critical to image processing of fundus images,which is precursor and essential first step to further analysis and diagnosis of diseases.However,this remains a challenge due to the noise and intensity variation in the background of fundus images.In this study,we propose a novel vessel segmentation approach using Hessian-based linear filter and entropic thresholding method to automatically segment vessels on fundus images.Firstly we adapt multi-scale linear filtering based on Hessian matrix to enhance vessels.Further,we generate a novel two-dimensional histogram to capture gray level and directional average gray level of linear neighborhood in results from filtering,and then the threshold values are determined by the maximum class entropies according to this histogram.Finally,the binary segmentation results for the vessels are achieved.The experiments demonstrate that,compared with two other methods,the proposed method can automatically yield more complete and accurate results.
查看全文查看/发表评论下载PDF阅读器
相关话题/重庆邮电大学 重庆 图像 中文 信息