2 citations · 2 across the 4 of their papers we have counts for
6 papers
Joint cardiac mapping and cardiac function estimation using a deep manifold framework
Qing Zou, Mathews Jacob
In this work, we proposed a continuous-acquisition strategy using a gradient echo (GRE) inversion recovery sequence based on spiral trajectories to simultaneously obtain the …
Dynamic imaging using a deep generative SToRM (Gen-SToRM) model
Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal +2
We introduce a generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic image data from highly undersampled measurements. The model assumes that…
Deep Generative SToRM model for dynamic imaging
Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal +2
We introduce a novel generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic image data from highly undersampled measurements. The proposed gene…
Recovery of surfaces and functions in high dimensions: sampling theory and links to neural networks
Qing Zou, Mathews Jacob
Several imaging algorithms including patch-based image denoising, image time series recovery, and convolutional neural networks can be thought of as methods that exploit the manifo…
Sampling of surfaces and functions in high dimensional spaces
Qing Zou, Mathews Jacob
We introduce a sampling theoretic framework for the recovery of smooth surfaces and functions living on smooth surfaces from few samples. The proposed approach can be thought of as…
Sampling of Planar Curves: Theory and Fast Algorithms
Qing Zou, Sunrita Poddar, Mathews Jacob
We introduce a continuous domain framework for the recovery of a planar curve from a few samples. We model the curve as the zero level set of a trigonometric polynomial. We show th…