A Novel Method for Computer Aided Plastic Surgery Prediction

Jie Liu, Xubo Yang, T. Xi, Lixu Gu, Zhe-yuan Yu
{"title":"A Novel Method for Computer Aided Plastic Surgery Prediction","authors":"Jie Liu, Xubo Yang, T. Xi, Lixu Gu, Zhe-yuan Yu","doi":"10.1109/BMEI.2009.5305021","DOIUrl":null,"url":null,"abstract":"In this paper, a novel method based on former cases for plastic surgery prediction is presented. This method takes a pre-operative frontal facial picture as an input. Landmarks of the face are then extracted and constitute a distance vector. As a set of facial parameters, such a vector is entered into either a sup- port vector regression (SVR) predictor or a k-nearest neighbor (KNN) predictor which is trained on a set of pre- and post- operative facial distance vectors of former cases. After the pre- dicted distance vector generated, new landmarks positions are updated and the final result is generated in terms of changes be- tween predicted landmarks and the original ones. Several expe- riments are carried out and the results show a great accuracy of prediction, which proves that this method is of high validity. Keywords-ASM; SVR; KNN; plastic surgery prediction","PeriodicalId":6389,"journal":{"name":"2009 2nd International Conference on Biomedical Engineering and Informatics","volume":"24 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2009.5305021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

In this paper, a novel method based on former cases for plastic surgery prediction is presented. This method takes a pre-operative frontal facial picture as an input. Landmarks of the face are then extracted and constitute a distance vector. As a set of facial parameters, such a vector is entered into either a sup- port vector regression (SVR) predictor or a k-nearest neighbor (KNN) predictor which is trained on a set of pre- and post- operative facial distance vectors of former cases. After the pre- dicted distance vector generated, new landmarks positions are updated and the final result is generated in terms of changes be- tween predicted landmarks and the original ones. Several expe- riments are carried out and the results show a great accuracy of prediction, which proves that this method is of high validity. Keywords-ASM; SVR; KNN; plastic surgery prediction
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
一种计算机辅助整形手术预测的新方法
本文提出了一种基于以往案例的整形手术预测新方法。该方法以术前额部面部图像作为输入。然后提取人脸的地标并构成距离向量。作为一组面部参数,该向量被输入支持向量回归(SVR)预测器或k近邻(KNN)预测器,该预测器在术前和术后病例的面部距离向量集上进行训练。在生成预测距离向量后,更新新的地标位置,并根据预测地标与原始地标之间的变化生成最终结果。实验结果表明,该方法具有较高的预测精度,具有较高的有效性。Keywords-ASM;SVR;资讯;整形手术预测
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
A Novel Approach for Blood Vessel Edge Detection in Retinal Images Skin Response During Irradiation by Intense Pulsed Light Based on Optical Imaging Technology and Histology Physical Properties of LYSO Scintillator for NN-PET Detectors A High Security Framework for SMS An Efficient Antenna Selection Algorithm for MIMO Systems
×
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