基于压痕曲线的超弹性模拟表面模型提取及其异常检测

Yingqiao Yang, K. Yung, Robert T. W. Hung, J. Foster, K. Yu
{"title":"基于压痕曲线的超弹性模拟表面模型提取及其异常检测","authors":"Yingqiao Yang, K. Yung, Robert T. W. Hung, J. Foster, K. Yu","doi":"10.1109/ISMR.2019.8710188","DOIUrl":null,"url":null,"abstract":"Manual palpation for the detection of anomalies is not possible through the small incisions of Robotic Minimally Invasive Surgery. The proposed novel approach allows robotic palpation by deforming the tissue surface with an indenter and analyzing the corresponding induced surface shape for indications of the abnormalities underneath. Three-dimensional hyperelastic finite element models were used to simulate the tool-tissue interaction of a hemispherical indenter pushing downwards onto the tissue surface. Curve fitting methods were employed to characterize the indentation curve of the deformed surface of either normal or abnormal tissue with an empirical equation. By analyzing these equations, we developed volume-based and gradient-based methods to investigate how the tumor position affects the surface deformation behavior of the tissue.The results of the simulations indicate that there are obvious differences in the surface deformation between healthy and diseased tissue, due to the higher stiffness of the tumor. A significant advantage of the proposed method is that it greatly broadens the detection area by providing estimates on the direction and distance of the tumor from the surrounding area of the indentation site, compared with previous studies only predicting the presence of a tumor in the contact area.","PeriodicalId":404745,"journal":{"name":"2019 International Symposium on Medical Robotics (ISMR)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Surface Model Extraction from Indentation Curves of Hyperelastic Simulation for Abnormality Detection\",\"authors\":\"Yingqiao Yang, K. Yung, Robert T. W. Hung, J. Foster, K. Yu\",\"doi\":\"10.1109/ISMR.2019.8710188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Manual palpation for the detection of anomalies is not possible through the small incisions of Robotic Minimally Invasive Surgery. The proposed novel approach allows robotic palpation by deforming the tissue surface with an indenter and analyzing the corresponding induced surface shape for indications of the abnormalities underneath. Three-dimensional hyperelastic finite element models were used to simulate the tool-tissue interaction of a hemispherical indenter pushing downwards onto the tissue surface. Curve fitting methods were employed to characterize the indentation curve of the deformed surface of either normal or abnormal tissue with an empirical equation. By analyzing these equations, we developed volume-based and gradient-based methods to investigate how the tumor position affects the surface deformation behavior of the tissue.The results of the simulations indicate that there are obvious differences in the surface deformation between healthy and diseased tissue, due to the higher stiffness of the tumor. A significant advantage of the proposed method is that it greatly broadens the detection area by providing estimates on the direction and distance of the tumor from the surrounding area of the indentation site, compared with previous studies only predicting the presence of a tumor in the contact area.\",\"PeriodicalId\":404745,\"journal\":{\"name\":\"2019 International Symposium on Medical Robotics (ISMR)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Symposium on Medical Robotics (ISMR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISMR.2019.8710188\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Symposium on Medical Robotics (ISMR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMR.2019.8710188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

通过机器人微创手术的小切口,手工触诊检测异常是不可能的。提出的新方法允许机器人触诊,通过用压头变形组织表面,并分析相应的诱导表面形状,以发现下面的异常迹象。采用三维超弹性有限元模型模拟了半球形压头向下推入组织表面时刀具与组织的相互作用。采用曲线拟合的方法,用经验方程对正常和异常组织变形表面的压痕曲线进行表征。通过分析这些方程,我们开发了基于体积和基于梯度的方法来研究肿瘤位置如何影响组织的表面变形行为。模拟结果表明,由于肿瘤的刚度较高,健康组织和病变组织的表面变形存在明显差异。该方法的一个显著优点是,与以往的研究只预测肿瘤在接触区域的存在相比,它通过提供肿瘤与压痕部位周围区域的方向和距离的估计,大大拓宽了检测范围。
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
Surface Model Extraction from Indentation Curves of Hyperelastic Simulation for Abnormality Detection
Manual palpation for the detection of anomalies is not possible through the small incisions of Robotic Minimally Invasive Surgery. The proposed novel approach allows robotic palpation by deforming the tissue surface with an indenter and analyzing the corresponding induced surface shape for indications of the abnormalities underneath. Three-dimensional hyperelastic finite element models were used to simulate the tool-tissue interaction of a hemispherical indenter pushing downwards onto the tissue surface. Curve fitting methods were employed to characterize the indentation curve of the deformed surface of either normal or abnormal tissue with an empirical equation. By analyzing these equations, we developed volume-based and gradient-based methods to investigate how the tumor position affects the surface deformation behavior of the tissue.The results of the simulations indicate that there are obvious differences in the surface deformation between healthy and diseased tissue, due to the higher stiffness of the tumor. A significant advantage of the proposed method is that it greatly broadens the detection area by providing estimates on the direction and distance of the tumor from the surrounding area of the indentation site, compared with previous studies only predicting the presence of a tumor in the contact area.
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
A Novel Task-Specific Upper-Extremity Rehabilitation System with Interactive Game-Based Interface for Stroke Patients A Multirobots Teleoperated Platform for Artificial Intelligence Training Data Collection in Minimally Invasive Surgery Automatic Detection of Needle Puncture in a Simulated Cannulation Task Concept Development of Fixed Geometry Tactile Display using Granular Jamming Optimizing Robot-Assisted Surgery Suture Plans to Avoid Joint Limits and Singularities
×
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