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02/03/2020
Atomic Super-Resolution Tomography
We consider the problem of reconstructing a nanocrystal at atomic resolu...
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05/12/2019
A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning
Unlike previous works, this open data collection consists of X-ray cone-...
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08/28/2018
A Multi-channel DART Algorithm
Tomography deals with the reconstruction of objects from their projectio...
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07/09/2018
Approximate k-space models and Deep Learning for fast photoacoustic reconstruction
We present a framework for accelerated iterative reconstructions using a...
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05/21/2018
Never look back - A modified EnKF method and its application to the training of neural networks without back propagation
In this work, we present a new derivative-free optimization method and i...
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05/21/2018
Never look back - The EnKF method and its application to the training of neural networks without back propagation
In this work, we present a new derivative-free optimization method and i...
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03/14/2018
Real-time Cardiovascular MR with Spatio-temporal De-aliasing using Deep Learning - Proof of Concept in Congenital Heart Disease
PURPOSE: Real-time assessment of ventricular volumes requires high accel...
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03/14/2018
Spatio-temporal Deep De-aliasing for Prospective Assessment of Real-time Ventricular Volumes
PURPOSE: Real-time assessment of ventricular volumes requires high accel...
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10/24/2017
A hierarchical Bayesian perspective on majorization-minimization for non-convex sparse regression: application to M/EEG source imaging
Majorization-minimization (MM) is a standard iterative optimization tech...
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08/31/2017