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Purpose: Oscillating gradient spin-echo (OGSE) diffusion MRI provides information about the microstructure of biological tissues via the frequency dependence of the apparent diffusion coefficient (ADC). ADC dependence on OGSE frequency has…
Diffusion kurtosis imaging is an extension of diffusion tensor imaging that provides scientifically and clinically valuable information about brain tissue microstructure but suffers from poor robustness to noise, especially in voxels…
Pulsar timing arrays (PTAs) have made tremendous progress and are now showing strong evidence for the gravitational-wave background (GWB). Further probing the origin and characteristics of the GWB will require more generalized analysis…
The purpose of this study is to propose a brain tissue-selective, optimized slice-by-slice B0 field shimming for high-resolution brain diffusion MRI. We incorporated actual gradient fields of X, Y, and Z gradient coils in the calculation of…
Changes in the nervous system due to neurological diseases take place at very small spatial scales, on the order of the micro and nanometers. Developing non-invasive imaging methods for obtaining this microscopic information as quantitative…
Purpose: Diffusion MRI (dMRI) suffers from eddy currents induced by strong diffusion gradients, which introduce artefacts that can impair subsequent diffusion metric analysis. Existing retrospective correction techniques that correct for…
Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning and monitoring of many neurological…
Frequency-dependent diffusion MRI (dMRI) using oscillating gradient encoding and diffusion kurtosis imaging (DKI) techniques have been shown to provide additional insight into tissue microstructure compared to conventional dMRI. However, a…
Heterogeneous diffusion processes are prevalent in various fields, including the motion of proteins in living cells, the migratory movement of birds and mammals, and finance. These processes are often characterized by time-varying dynamics,…
Orthogonal time-frequency space (OTFS) modulation is a recently proposed waveform for efficient data transfer in high-speed vehicular scenarios. The use of rectangular pulse shape in OTFS results in high out of band (OoB) radiation, which…
Purpose: The impact of microscopic diffusional kurtosis ($\mu K$) - arising from restricted diffusion and/or structural disorder - remains a controversial issue in contemporary diffusion MRI (dMRI). Recently, Correlation Tensor MRI (CTI)…
Magnetic resonance microscopy images at cellular resolution (< 10 microns) are limited by diffusion. SNR and spatial resolution suffer from the dephasing of transverse magnetization caused by diffusion of spins in strong gradients. Such…
Objective: Most deep neural network-based diffusion tensor imaging methods require the diffusion gradients' number and directions in the data to be reconstructed to match those in the training data. This work aims to develop and evaluate a…
CT perfusion imaging (CTP) is used in the diagnostic workup of acute ischemic stroke (AIS). CTP may be performed within the angio suite using flat detector CT (FDCT) to help reduce patient management time. In order to significantly improve…
Diffusion models have been used for probabilistic time series forecasting and show strong potential. However, fixed noise schedules often produce intermediate states that are hard to invert and a terminal state that deviates from the near…
A Discrete Fourier Transform Method (DFTM) for discrimination between the signal of neutrons and gamma rays in organic scintillation detectors is presented. The method is based on the transformation of signals into the frequency domain…
Purpose: To develop a 3D distortion-free reduced-FOV diffusion-prepared GRE sequence and demonstrate its in-vivo application for diffusion imaging of the spinal cord in healthy volunteers. Methods: A 3D multi-shot reduced-FOV…
Due to recent technological advances, large brain imaging data sets can now be collected. Such data are highly complex so extraction of meaningful information from them remains challenging. Thus, there is an urgent need for statistical…
In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting inter-symbol interference (ISI)…
Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sensor failures and irregular sampling lead to pervasive missing values. However, existing…