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

页码：728 / 731

页数：4

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