.png){kind=icon}
返回
1D inverse problem in diffusion based optical tomography using iteratively regularized Gauss-Newton algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.amc.2003.12.019.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we investigate an one-dimensional inverse problem in diffusion based optical tomography using iteratively regularized Gauss-Newton (IRGN) algorithm for ill-posed nonlinear problems. We devise a stable reconstruction algorithm for the inverse problem using iterative regularization with Armijo-Goldstein-Wolf (AGW) type line search strategy. We demonstrate the efficacy of the IRGN combined with AGW by reconstructing the scattering parameter relevant to the inverse problem in optical tomography. (C) 2003 Elsevier Inc. All rights reserved.
Keyword:
inverse problems
nonlinear ill-posed
iteratively regularized Gauss-Newton
biomedical imaging
reconstruction algorithms
期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏分享收藏
查看更多内容