We present a fast method for generating random samples according to a variable density
poisson-disc distribution. A minimum parameter value is used to create a background grid …

Purpose We present a method that combines compressed sensing with parallel imaging that
takes advantage of the structure of the sparsifying transformation. Approach Previous work …

We propose a random Fourier sampling scheme to enhance the accuracy of the high
frequency pattern estimation for image reconstruction. This method is designed to work in a …

We present a novel endoscopy probe using optical coherence tomography (OCT) that
combines sparse Lissajous scanning and compressed sensing (CS) for faster data …

Abstract The non-uniform Discrete Fourier Transform algorithm has shown great utility for
reconstructing images from non-uniformly spaced Fourier samples in several imaging …

The fast and reliable processing of medical images is of paramount importance to
adequately generate data to feed machine learning algorithms that can prevent and …

In this paper, we review physics-and data-driven reconstruction techniques for simultaneous
positron emission tomography (PET)/magnetic resonance imaging (MRI) systems, which …

MRI T2 mapping sequences quantitatively assess tissue health and depict early
degenerative changes in musculoskeletal (MSK) tissues like cartilage and intervertebral …

The discrete curvelet transform decomposes an image into a set of fundamental components
that are distinguished by direction and size and a low-frequency representation. The …

With Fourier sensing, it is commonly the case that the field-of-view (FOV), the area of space
to be imaged, is known prior to reconstruction. To date, reconstruction algorithms have …