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Neuroimaging studies aim to analyze imaging data with complex spatial patterns in a large number of locations (called voxels) on a two-dimensional (2D) surface or in a 3D volume. Conventional analyses of imaging data include two sequential steps: spatially smoothing imaging data and then independently fitting a statistical model at each voxel. However,(More)
Twin imaging studies have been valuable for understanding the relative contribution of the environment and genes on brain structures and their functions. Conventional analyses of twin imaging data include three sequential steps: spatially smoothing imaging data, independently fitting a structural equation model at each voxel, and finally correcting for(More)
PURPOSE To use functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to investigate visual system development in children being treated for retinoblastoma. METHODS Informed consent was obtained for all participants (N = 42) in this institutional review board-approved study. Participants were imaged with a 1.5-T scanner while(More)
Many large-scale longitudinal imaging studies have been or are being widely conducted to better understand the progress of neuropsychiatric and neurodegenerative disorders and normal brain development. The goal of this article is to develop a multiscale adaptive generalized estimation equation (MAGEE) method for spatial and adaptive analysis of neuroimaging(More)
Stochastic noise, susceptibility artifacts, magnetic field and radiofrequency inhomogeneities, and other noise components in magnetic resonance images (MRIs) can introduce serious bias into any measurements made with those images. We formally introduce three regression models including a Rician regression model and two associated normal models to(More)
PURPOSE To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. METHODS A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes(More)
The aim of this paper is to develop an intrinsic regression model for the analysis of positive-definite matrices as responses in a Riemannian manifold and their association with a set of covariates, such as age and gender, in a Euclidean space. The primary motivation and application of the proposed methodology is in medical imaging. Because the set of(More)
OBJECTIVE The study objective is to evaluate the feasibility and efficacy of a web-based intervention for parents (AfterTheInjury.org [ATI]) in promoting emotional recovery following pediatric injury. METHODS 100 children with injuries requiring medical attention and their parents were randomly assigned to the intervention or usual care. Efficacy outcomes(More)
OBJECTIVE We conducted a randomized, double-blind, placebo-controlled efficacy and tolerability trial of Matricaria recutita (chamomile) extract therapy in patients with mild to moderate generalized anxiety disorder (GAD). We hypothesized that chamomile would be superior to placebo in reducing GAD symptoms with a comparable tolerability profile. MATERIALS(More)
We develop a novel statistical model, called multiscale adaptive regression model (MARM), for spatial and adaptive analysis of neuroimaging data. The primary motivation and application of the proposed methodology is statistical analysis of imaging data on the two-dimensional (2D) surface or in the 3D volume for various neuroimaging studies. The existing(More)