[POSTER]基于多剪影图像的弹性体内窥镜图像增强变形估计

Akira Saito, M. Nakao, Yuuki Uranishi, T. Matsuda
{"title":"[POSTER]基于多剪影图像的弹性体内窥镜图像增强变形估计","authors":"Akira Saito, M. Nakao, Yuuki Uranishi, T. Matsuda","doi":"10.1109/ISMAR.2015.49","DOIUrl":null,"url":null,"abstract":"This study proposes a method to estimate elastic deformation using silhouettes obtained from multiple endoscopic images. Our method can estimate the intraoperative deformation of organs using a volumetric mesh model reconstructed from preoperative CT data. We use this elastic body silhouette information of elastic bodies not to model the shape but to estimate the local displacements. The model shape is updated to satisfy the silhouette constraint while preserving the shape as much as possible. The result of the experiments showed that the proposed methods could estimate the deformation with root mean square (RMS) errors of 5.0–10 mm.","PeriodicalId":240196,"journal":{"name":"2015 IEEE International Symposium on Mixed and Augmented Reality","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"[POSTER] Deformation Estimation of Elastic Bodies Using Multiple Silhouette Images for Endoscopic Image Augmentation\",\"authors\":\"Akira Saito, M. Nakao, Yuuki Uranishi, T. Matsuda\",\"doi\":\"10.1109/ISMAR.2015.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study proposes a method to estimate elastic deformation using silhouettes obtained from multiple endoscopic images. Our method can estimate the intraoperative deformation of organs using a volumetric mesh model reconstructed from preoperative CT data. We use this elastic body silhouette information of elastic bodies not to model the shape but to estimate the local displacements. The model shape is updated to satisfy the silhouette constraint while preserving the shape as much as possible. The result of the experiments showed that the proposed methods could estimate the deformation with root mean square (RMS) errors of 5.0–10 mm.\",\"PeriodicalId\":240196,\"journal\":{\"name\":\"2015 IEEE International Symposium on Mixed and Augmented Reality\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Symposium on Mixed and Augmented Reality\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISMAR.2015.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Symposium on Mixed and Augmented Reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMAR.2015.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

摘要

本研究提出了一种利用从多个内窥镜图像中获得的轮廓来估计弹性变形的方法。我们的方法可以利用术前CT数据重建的体积网格模型来估计术中器官的变形。我们利用弹性体的轮廓信息来估计局部位移,而不是建立弹性体的形状模型。模型形状被更新以满足轮廓约束,同时尽可能地保留形状。实验结果表明,该方法可以估计变形,均方根误差(RMS)为5.0±10 mm。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
[POSTER] Deformation Estimation of Elastic Bodies Using Multiple Silhouette Images for Endoscopic Image Augmentation
This study proposes a method to estimate elastic deformation using silhouettes obtained from multiple endoscopic images. Our method can estimate the intraoperative deformation of organs using a volumetric mesh model reconstructed from preoperative CT data. We use this elastic body silhouette information of elastic bodies not to model the shape but to estimate the local displacements. The model shape is updated to satisfy the silhouette constraint while preserving the shape as much as possible. The result of the experiments showed that the proposed methods could estimate the deformation with root mean square (RMS) errors of 5.0–10 mm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
[POSTER] Realtime Shape-from-Template: System and Applications [POSTER] Geometric Mapping for Color Compensation Using Scene Adaptive Patches Auditory and Visio-Temporal Distance Coding for 3-Dimensional Perception in Medical Augmented Reality [POSTER] Mixed-Reality Store on the Other Side of a Tablet A Framework to Evaluate Omnidirectional Video Coding Schemes
×
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