在肠道和口腔颌面外科远程呈现中使用混合现实技术的新方案:三维平均值克隆算法。

Arjina Maharjan, Abeer Alsadoon, P W C Prasad, Nada AlSallami, Tarik A Rashid, Ahmad Alrubaie, Sami Haddad
{"title":"在肠道和口腔颌面外科远程呈现中使用混合现实技术的新方案:三维平均值克隆算法。","authors":"Arjina Maharjan, Abeer Alsadoon, P W C Prasad, Nada AlSallami, Tarik A Rashid, Ahmad Alrubaie, Sami Haddad","doi":"10.1002/rcs.2161","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and aim: </strong>Most of the Mixed Reality models used in the surgical telepresence are suffering from the discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts.</p><p><strong>Methodology: </strong>The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discoloration artefacts around the blending region RESULTS: As compared to the state of art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds CONCLUSION: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video. This article is protected by copyright. All rights reserved.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":" ","pages":"e2161"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm.\",\"authors\":\"Arjina Maharjan, Abeer Alsadoon, P W C Prasad, Nada AlSallami, Tarik A Rashid, Ahmad Alrubaie, Sami Haddad\",\"doi\":\"10.1002/rcs.2161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and aim: </strong>Most of the Mixed Reality models used in the surgical telepresence are suffering from the discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts.</p><p><strong>Methodology: </strong>The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discoloration artefacts around the blending region RESULTS: As compared to the state of art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds CONCLUSION: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video. This article is protected by copyright. All rights reserved.</p>\",\"PeriodicalId\":75029,\"journal\":{\"name\":\"The international journal of medical robotics + computer assisted surgery : MRCAS\",\"volume\":\" \",\"pages\":\"e2161\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The international journal of medical robotics + computer assisted surgery : MRCAS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/rcs.2161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The international journal of medical robotics + computer assisted surgery : MRCAS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/rcs.2161","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

背景和目的:由于视频帧中的光照变化,大多数用于远程呈现手术的混合现实模型都存在边界区域差异和时空不一致的问题。这项工作的目的是提出一种新的解决方案,通过合并手术现场的增强视频和远程专业外科医生的虚拟手来帮助生成复合视频。提出解决方案的目的是减少叠加和可视化误差,消除遮挡和伪影,从而缩短处理时间,提高合并视频的准确性:拟议的系统增强了平均值克隆算法,有助于保持最终合成视频的时空一致性。增强算法包括图像克隆过程中的三维均值坐标和改进的均值插值法,有助于减少混合区域周围的锯齿、污点和变色伪影 结果:与现有解决方案相比,拟议解决方案的叠加误差精度从 1.01 毫米提高到 0.80 毫米,可视化误差精度从 98.8%提高到 99.4%。处理时间从 0.211 秒缩短到 0.173 秒 结论:我们的解决方案通过增加空间距离,使感兴趣对象与目标图像的光强度保持一致,从而有助于保持最终合并视频的空间一致性。本文受版权保护。保留所有权利。
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
A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm.

Background and aim: Most of the Mixed Reality models used in the surgical telepresence are suffering from the discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts.

Methodology: The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discoloration artefacts around the blending region RESULTS: As compared to the state of art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds CONCLUSION: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video. This article is protected by copyright. All rights reserved.

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
CiteScore
5.30
自引率
0.00%
发文量
0
期刊最新文献
Multi-Objective Safety-Enhanced Path Planning for the Anterior Part of a Flexible Ureteroscope in Robot-Assisted Surgery. Validation of an Augmented Reality Based Functional Method to Determine and Render the Hip Rotation Centre During Total Hip Arthroplasty. Comparison of robotic and open central pancreatectomy. Full coverage path planning algorithm for MRgFUS therapy A deep learning framework for real‐time 3D model registration in robot‐assisted laparoscopic surgery
×
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