A Kernel Ridge Regression Model for Respiratory Motion Estimation in Radiotherapy
نویسندگان
چکیده
This paper discusses a kernel ridge regression (KRR) model for motion estimation in radiotherapy. Using KRR, dense internal motion fields are estimated from high-dimensional surrogates without the need for prior dimensionality reduction. We compare the proposed model to a related approach with dimensionality reduction in the form of principal component analysis and principle component regression. Evaluation was performed in a simulation study based on nine 4D CT patient data sets achieving a mean estimation error of 0.84 ± 0.21 mm for our approach.
منابع مشابه
A MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION
This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...
متن کاملNonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data
The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...
متن کاملA fast model for prediction of respiratory lung motion for image-guided radiotherapy: A feasibility study
Background: The aim of this work was to study the feasibility of constructing a fast thorax model suitable for simulating lung motion due to respiration using only one CT dataset. Materials and Methods: For each of six patients with different thorax sizes, two sets of CT images were obtained in single-breath-hold inhale and exhale stages in the supine position. The CT images were then ...
متن کاملGeneralized Ridge Regression Estimator in Semiparametric Regression Models
In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...
متن کاملKernel Ridge Estimator for the Partially Linear Model under Right-Censored Data
Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity and censorship. To address these issues, we improved the kernel estimator based on synthetic data transformation and kNN imputation techniques. The key idea of this paper is t...
متن کامل