no code implementations • 12 Jun 2021 • Nicholas Dwork, Daniel O'Connor, Ethan M. I. Johnson, Corey A. Baron, Jeremy W. Gordon, John M. Pauly, Peder E. Z. Larson
The Gridding algorithm has shown great utility for reconstructing images from non-uniformly spaced samples in the Fourier domain in several imaging modalities.
no code implementations • 24 Dec 2020 • Daniel O'Connor, Walter Vinci
We show that D-Flow achieves similar likelihoods and FID/IS scores to those of a typical IF with Gaussian base variables, but with the additional benefit that global features are meaningfully encoded as discrete labels in the latent space.
no code implementations • 19 Aug 2020 • Tanishq Abraham, Andrew Shaw, Daniel O'Connor, Austin Todd, Richard Levenson
In order to bridge the gap between MUSE and traditional histology, we aim to convert MUSE images to resemble authentic hematoxylin- and eosin-stained (H&E) images.
no code implementations • 1 Jul 2020 • Nicholas Dwork, Ethan M. I. Johnson, Daniel O'Connor, Jeremy W. Gordon, Adam B. Kerr, Corey A. Baron, John M. Pauly, Peder E. Z. Larson
In this manuscript, we present a generalization of several existing iterative model based algorithms.
no code implementations • 14 Apr 2020 • Nicholas Dwork, Corey A. Baron, Ethan M. I. Johnson, Daniel O'Connor, John M. Pauly, Peder E. Z. Larson
We present a fast method for generating random samples according to a variable density Poisson-disc distribution.
no code implementations • 11 Mar 2020 • Nicholas Dwork, Jeremy W. Gordon, Shuyu Tang, Daniel O'Connor, Esben Sovso Szocska Hansen, Christoffer Laustsen, Peder E. Z. Larson
Magnetic resonance imaging with hyperpolarized contrast agents can provide unprecedented \textit{in-vivo} measurements of metabolism, but yields images that are lower resolution than that achieved with proton anatomical imaging.
no code implementations • 11 Feb 2020 • Nicholas Dwork, Daniel O'Connor, Corey A. Baron, Ethan M. I. Johnson, Adam B. Kerr, John M. Pauly, Peder E. Z. Larson
In this work, we take advantage of the structure of this wavelet transform and identify an affine transformation that increases the sparsity of the result.
1 code implementation • 22 Jul 2017 • Ningning Zhao, Daniel O'Connor, Adrian Basarab, Dan Ruan, Peng Hu, Ke Sheng
This paper proposes a novel framework to reconstruct the dynamic magnetic resonance images (DMRI) with motion compensation (MC).