Graph-based optimal multi-surface segmentation with a star-shaped prior: Application to the segmentation of the optic disc and cup

Junjie Bai, Mohammad Saleh Miri, Yinxiao Liu, P. Saha, M. Garvin, Xiaodong Wu
{"title":"Graph-based optimal multi-surface segmentation with a star-shaped prior: Application to the segmentation of the optic disc and cup","authors":"Junjie Bai, Mohammad Saleh Miri, Yinxiao Liu, P. Saha, M. Garvin, Xiaodong Wu","doi":"10.1109/ISBI.2014.6867924","DOIUrl":null,"url":null,"abstract":"A novel graph-based optimal segmentation method which can simultaneously segment multiple star-shaped surfaces is presented in this paper. Minimum and maximum surface distance constraints can be enforced between different surfaces. In addition, the segmented surfaces are ensured to be smooth by incorporating surface smoothness constraints which limit the variation between adjacent surface voxels. A consistent digital ray system is utilized to make sure the segmentation result is star-shaped and consistent, without interpolating image as required by other methods. To the best of our knowledge, the concept of consistent digital rays is for the first time introduced into the field of medical imaging. The problem is formulated as an MRF optimization problem which can be efficiently and exactly solved by computing a single min s-t cut in an appropriately constructed graph. The method is applied to the segmentation of the optic disc and cup on 70 registered fundus and SD-OCT images from glaucoma patients. The result shows improved accuracy by applying the proposed method (versus using a classification-based approach).","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2014.6867924","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

Abstract

A novel graph-based optimal segmentation method which can simultaneously segment multiple star-shaped surfaces is presented in this paper. Minimum and maximum surface distance constraints can be enforced between different surfaces. In addition, the segmented surfaces are ensured to be smooth by incorporating surface smoothness constraints which limit the variation between adjacent surface voxels. A consistent digital ray system is utilized to make sure the segmentation result is star-shaped and consistent, without interpolating image as required by other methods. To the best of our knowledge, the concept of consistent digital rays is for the first time introduced into the field of medical imaging. The problem is formulated as an MRF optimization problem which can be efficiently and exactly solved by computing a single min s-t cut in an appropriately constructed graph. The method is applied to the segmentation of the optic disc and cup on 70 registered fundus and SD-OCT images from glaucoma patients. The result shows improved accuracy by applying the proposed method (versus using a classification-based approach).
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
星形先验的基于图的最优多面分割:视盘和视杯分割的应用
提出了一种基于图的多星形曲面同时分割的优化分割方法。最小和最大表面距离约束可以在不同的表面之间强制执行。此外,通过结合表面平滑约束来限制相邻表面体素之间的变化,确保分割的表面是光滑的。采用一致的数字射线系统,使分割结果呈星形一致,不需要像其他方法那样对图像进行插值。据我们所知,一致数字射线的概念是第一次引入医学成像领域。该问题被表述为一个MRF优化问题,该问题可以通过在一个适当构造的图中计算单个最小s-t切割来有效而精确地求解。应用该方法对70例青光眼患者眼底和SD-OCT图像进行视盘和视杯的分割。结果表明,应用所提出的方法(与使用基于分类的方法相比)提高了准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
MRI based attenuation correction for PET/MRI via MRF segmentation and sparse regression estimated CT DTI-DeformIt: Generating ground-truth validation data for diffusion tensor image analysis tasks Functional parcellation of the hippocampus by clustering resting state fMRI signals Detecting cell assembly interaction patterns via Bayesian based change-point detection and graph inference model Topological texture-based method for mass detection in breast ultrasound image
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1