Ptychography is an enabling microscopy technique for both fundamental and applied
sciences. In the past decade, it has become an indispensable imaging tool in most X-ray …

Artificial Intelligence (Al) models are being produced and used to solve a variety of current
and future business and technical problems. Therefore, AI model engineering processes …

Recent efforts on solving inverse problems in imaging via deep neural networks use
architectures inspired by a fixed number of iterations of an optimization method. The number …

Purpose To develop a strategy for training a physics‐guided MRI reconstruction neural
network without a database of fully sampled data sets. Methods Self‐supervised learning via …

We propose Coordinate-based Internal Learning (CoIL) as a new deep-learning (DL)
methodology for continuous representation of measurements. Unlike traditional DL methods …

Physics-driven deep learning methods have emerged as a powerful tool for computational
magnetic resonance imaging (MRI) problems, pushing reconstruction performance to new …

Video snapshot compressive imaging (SCI) captures a sequence of video frames in a single
shot using a 2D detector. The underlying principle is that during one exposure time, different …

Cardiovascular disease is a major cause of death worldwide. Computed Tomography
Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery …

Computational imaging systems algorithmically post-process acquisition images either to
reveal physical quantities of interest or to increase image quality, eg, deblurring. Designing …

Abstract Plug-and-Play Priors (PnP) and Regularization by Denoising (RED) are widely-
used frameworks for solving imaging inverse problems by computing fixed-points of …