Publications (57)
3D FLAT: Feasible Learned Acquisition Trajectories for Accelerated MRI
Jonathan Alush-Aben, Linor Ackerman-Schraier, Tomer Weiss +3
Magnetic Resonance Imaging (MRI) has long been considered to be among the gold standards of today's diagnostic imaging. The most significant drawback of MRI is long acquisition tim…
Image reconstruction from dense binary pixels
Or Litany, Tal Remez, Alex Bronstein
Recently, the dense binary pixel Gigavision camera had been introduced, emulating a digital version of the photographic film. While seems to be a promising solution for HDR imaging…
Random Forests Can Hash
Qiang Qiu, Guillermo Sapiro, Alex Bronstein
Hash codes are a very efficient data representation needed to be able to cope with the ever growing amounts of data. We introduce a random forest semantic hashing scheme with infor…
T1-PILOT: Optimized Trajectories for T1 Mapping Acceleration
Tamir Shor, Moti Freiman, Chaim Baskin +1
Cardiac T1 mapping provides critical quantitative insights into myocardial tissue composition, enabling the assessment of pathologies such as fibrosis, inflammation, and edema. How…
Horizontal Flows and Manifold Stochastics in Geometric Deep Learning
Stefan Sommer, Alex Bronstein
We introduce two constructions in geometric deep learning for 1) transporting orientation-dependent convolutional filters over a manifold in a continuous way and thereby defining a…
Self-Supervised Classification Network
Elad Amrani, Leonid Karlinsky, Alex Bronstein
We present Self-Classifier -- a novel self-supervised end-to-end classification learning approach. Self-Classifier learns labels and representations simultaneously in a single-stag…