Asymptotic Normality of Kernel Estimators for Images Observed under the Radon Transform in Fan Beam Design

被引：0
|
作者：
Proksch, Katharina [1 ]
机构：
[1] Ruhr Univ Bochum, Fak Math, D-44780 Bochum, Germany
来源：
11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013, PTS 1 AND 2 (ICNAAM 2013) | 2013年 / 1558卷
关键词：
Inverse problems; Multivariate regression; Nonparametric regression; Radon transform;
D O I：
10.1063/1.4825596
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We consider a nonparametric, two-dimensional regression model that describes observations of Radon transformed images, i.e., an inverse regression model. Reconstructions from deterministic fan beam design by a certain kind of kernel-type estimators are considered and their asymptotic properties are investigated. The problem discussed is related to medical imaging procedures such as computerized tomography (CT).
引用
收藏
页码：728 / 731
页数：4
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