We propose a class of estimation techniques for scalar-on-function regression where both outcomes and functional predictors may be observed at multiple visits. Our methods are motivated by a longitudinal brain diffusion tensor imaging tractography study. One of the study's primary goals is to evaluate the contemporaneous association between human function and brain imaging over time. The comple...

3 Telsa MR scanners are now becoming more widely available and 3 Telsa is likely to become the filed strength of choice for clinical imaging of the brain. The neonatal brain can be safely and successfully imaged at 3 Telsa. The improved signal to noise afforded by a higher field strength may be used to improve image quality or shorten acquisition times. This may be exploited for conventional T1...

Conventional MR, diffusion-weighted, and diffusion tensor imaging were performed in an 8-day-old girl with citrullinemia. She had severe hyperammonemia for several days. On conventional T2-weighted MR images, symmetric, confluent high signal intensity was found in the bilateral thalami, basal ganglia, cortex, and subcortical white matter. Diffusion-weighted imaging demonstrated decreased appare...

We evaluate a recent statistical tractography technique for analyzing the diffusion tensor imaging data using new criteria and the template from the Tractometer. This novel method simultaneously achieves excellent percentages on 3 out of 7 criteria. Compared to deterministic tractography methods, it is superior to all of them. Compared to probabilistic tractography methods, it has similar resul...

While holding vast potential, diffusion tensor imaging (DTI) with single-excitation protocols still faces serious challenges. Limited spatial resolution, susceptibility to magnetic field inhomogeneity, and low signal-to-noise ratio (SNR) may be considered the most prominent limitations. It is demonstrated that all of these shortcomings can be effectively mitigated by the transition to parallel ...

Introduction Diffusion kurtosis tensor imaging provides additional information compared with diffusion tensor imaging [1,2]. Solving the kurtosis tensor, however, requires measurements in at least 15 diffusion-encoding directions as well as measurements with at least three or more b-values in each of these directions [2]. This leads to scanning times in the order of 6-10 minutes, which is often...

Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that provides an indirect measure of neuronal activity by detecting blood flow changes, has experienced an explosive growth in the past years. Statistical methods play a crucial role in understanding and analyzing fMRI data. Bayesian approaches, in particular, have shown great promise in applications. A remarkable f...

We consider dependent functional data that are correlated because of a longitudinal-based design: each subject is observed at repeated times and at each time a functional observation (curve) is recorded. We propose a novel parsimonious modeling framework for repeatedly observed functional observations that allows to extract low dimensional features. The proposed methodology accounts for the lon...

Diffusion tensor imaging (DTI) data differ fundamentally from most brain imaging data in that values at each voxel are not scalars but 3 x 3 positive definite matrices also called diffusion tensors. Frequently, investigators simplify the data analysis by reducing the tensor to a scalar, such as fractional anisotropy (FA). New statistical methods are needed for analyzing vector and tensor valued...