32 citations · 38 across the 3 of their papers we have counts for
6 papers · 1 filter
Texture and Structure Two-view Classification of Images
Samah Khawaled, Michael Zibulevsky, Yehoshua Y. Zeevi
Textural and structural features can be regraded as "two-view" feature sets. Inspired by the recent progress in multi-view learning, we propose a novel two-view classification meth…
Learning beamforming in ultrasound imaging
Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov +3
Medical ultrasound (US) is a widespread imaging modality owing its popularity to cost efficiency, portability, speed, and lack of harmful ionizing radiation. In this paper, we demo…
High frame-rate cardiac ultrasound imaging with deep learning
Ortal Senouf, Sanketh Vedula, Grigoriy Zurakhov +5
Cardiac ultrasound imaging requires a high frame rate in order to capture rapid motion. This can be achieved by multi-line acquisition (MLA), where several narrow-focused received…
High quality ultrasonic multi-line transmission through deep learning
Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov +5
Frame rate is a crucial consideration in cardiac ultrasound imaging and 3D sonography. Several methods have been proposed in the medical ultrasound literature aiming at acceleratin…
Towards CT-quality Ultrasound Imaging using Deep Learning
Sanketh Vedula, Ortal Senouf, Alex M. Bronstein +2
The cost-effectiveness and practical harmlessness of ultrasound imaging have made it one of the most widespread tools for medical diagnosis. Unfortunately, the beam-forming based i…
A Deep Learning Approach to Block-based Compressed Sensing of Images
Amir Adler, David Boublil, Michael Elad +1
Compressed sensing (CS) is a signal processing framework for efficiently reconstructing a signal from a small number of measurements, obtained by linear projections of the signal.…