非线性层析医学成像问题的伴随场方法

E. L. Miller, Kate Boverman
{"title":"非线性层析医学成像问题的伴随场方法","authors":"E. L. Miller, Kate Boverman","doi":"10.1109/ICIP.2002.1040030","DOIUrl":null,"url":null,"abstract":"We show results for full three-dimensional non-linear inversion of the parameters of a diffusive partial differential equation, specifically for an optical tomography application. We compute functional derivatives of the parameters with respect to the mean-squared error using the adjoint field method, and implement two forms of regularization. In the first, a penalty term is introduced into the error functional, and in the second, the solution to the inverse problem is assumed to belong to a parametrized class of functions. In the case where this assumption is correct, our results demonstrate that the parameters can recovered with high accuracy, yielding a better inversion result than the traditional Tikhonov-type approach.","PeriodicalId":74572,"journal":{"name":"Proceedings. International Conference on Image Processing","volume":"30 1","pages":"II-II"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adjoint field methods for non-linear tomographic medical imaging problems\",\"authors\":\"E. L. Miller, Kate Boverman\",\"doi\":\"10.1109/ICIP.2002.1040030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show results for full three-dimensional non-linear inversion of the parameters of a diffusive partial differential equation, specifically for an optical tomography application. We compute functional derivatives of the parameters with respect to the mean-squared error using the adjoint field method, and implement two forms of regularization. In the first, a penalty term is introduced into the error functional, and in the second, the solution to the inverse problem is assumed to belong to a parametrized class of functions. In the case where this assumption is correct, our results demonstrate that the parameters can recovered with high accuracy, yielding a better inversion result than the traditional Tikhonov-type approach.\",\"PeriodicalId\":74572,\"journal\":{\"name\":\"Proceedings. International Conference on Image Processing\",\"volume\":\"30 1\",\"pages\":\"II-II\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2002.1040030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2002.1040030","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

我们展示了扩散偏微分方程参数的全三维非线性反演结果,特别是用于光学层析成像应用。利用伴随域法计算参数对均方误差的泛函导数,并实现两种形式的正则化。首先,在误差泛函中引入惩罚项;其次,假设反问题的解属于参数化的函数类。在此假设正确的情况下,我们的结果表明,参数可以以较高的精度恢复,产生比传统的Tikhonov-type方法更好的反演结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adjoint field methods for non-linear tomographic medical imaging problems
We show results for full three-dimensional non-linear inversion of the parameters of a diffusive partial differential equation, specifically for an optical tomography application. We compute functional derivatives of the parameters with respect to the mean-squared error using the adjoint field method, and implement two forms of regularization. In the first, a penalty term is introduced into the error functional, and in the second, the solution to the inverse problem is assumed to belong to a parametrized class of functions. In the case where this assumption is correct, our results demonstrate that the parameters can recovered with high accuracy, yielding a better inversion result than the traditional Tikhonov-type approach.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信