6 papers
Joint optimization of system design and reconstruction in MIMO radar imaging
Tomer Weiss, Nissim Peretz, Sanketh Vedula +2
Multiple-input multiple-output (MIMO) radar is one of the leading depth sensing modalities. However, the usage of multiple receive channels lead to relative high costs and prevent…
Towards learned optimal q-space sampling in diffusion MRI
Tomer Weiss, Sanketh Vedula, Ortal Senouf +2
Fiber tractography is an important tool of computational neuroscience that enables reconstructing the spatial connectivity and organization of white matter of the brain. Fiber trac…
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…
PILOT: Physics-Informed Learned Optimized Trajectories for Accelerated MRI
Tomer Weiss, Ortal Senouf, Sanketh Vedula +3
Magnetic Resonance Imaging (MRI) has long been considered to be among "the gold standards" of diagnostic medical imaging. The long acquisition times, however, render MRI prone to m…
Self-supervised learning of inverse problem solvers in medical imaging
Ortal Senouf, Sanketh Vedula, Tomer Weiss +3
In the past few years, deep learning-based methods have demonstrated enormous success for solving inverse problems in medical imaging. In this work, we address the following questi…
Joint learning of cartesian undersampling and reconstruction for accelerated MRI
Tomer Weiss, Sanketh Vedula, Ortal Senouf +3
Magnetic Resonance Imaging (MRI) is considered today the golden-standard modality for soft tissues. The long acquisition times, however, make it more prone to motion artifacts as w…