Medical image processing on the GPU–Past, present and future
Graphics processing units (GPUs) are used today in a wide range of applications, mainly
because they can dramatically accelerate parallel computing, are affordable and energy …
because they can dramatically accelerate parallel computing, are affordable and energy …
Fast imaging for hyperpolarized MR metabolic imaging
MRI with hyperpolarized carbon‐13 agents has created a new type of noninvasive, in vivo
metabolic imaging that can be applied in cell, animal, and human studies. The use of 13C …
metabolic imaging that can be applied in cell, animal, and human studies. The use of 13C …
A subspace approach to high‐resolution spectroscopic imaging
Purpose To accelerate spectroscopic imaging using sparse sampling of‐space and
subspace (or low‐rank) modeling to enable high‐resolution metabolic imaging with good …
subspace (or low‐rank) modeling to enable high‐resolution metabolic imaging with good …
Accelerating advanced MRI reconstructions on GPUs
Computational acceleration on graphics processing units (GPUs) can make advanced
magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings …
magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings …
High‐resolution 1H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction
Purpose To develop data acquisition and image reconstruction methods to enable high‐
resolution 1H MR spectroscopic imaging (MRSI) of the brain, using the recently proposed …
resolution 1H MR spectroscopic imaging (MRSI) of the brain, using the recently proposed …
Denoising MR spectroscopic imaging data with low-rank approximations
This paper addresses the denoising problem associated with magnetic resonance
spectroscopic imaging (MRSI), where signal-to-noise ratio (SNR) has been a critical …
spectroscopic imaging (MRSI), where signal-to-noise ratio (SNR) has been a critical …
Off-the-grid recovery of piecewise constant images from few Fourier samples
We introduce a method to recover a continuous domain representation of a piecewise
constant two-dimensional image from few low-pass Fourier samples. Assuming the edge set …
constant two-dimensional image from few low-pass Fourier samples. Assuming the edge set …
Removal of nuisance signals from limited and sparse 1H MRSI data using a union‐of‐subspaces model
Purpose To remove nuisance signals (eg, water and lipid signals) for 1H MRSI data
collected from the brain with limited and/or sparse (k, t)‐space coverage. Methods A union …
collected from the brain with limited and/or sparse (k, t)‐space coverage. Methods A union …
Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces
Purpose To develop a subspace learning method for the recently proposed subspace‐
based MRSI approach known as SPICE, and achieve ultrafast 1H‐MRSI of the brain. Theory …
based MRSI approach known as SPICE, and achieve ultrafast 1H‐MRSI of the brain. Theory …
Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging Utilizing Deep Learning
Magnetic resonance spectroscopic imaging (SI) is a unique imaging technique that provides
biochemical information from in vivo tissues. The 1H spectra acquired from several spatial …
biochemical information from in vivo tissues. The 1H spectra acquired from several spatial …