61 citations · 157 across the 19 of their papers we have counts for
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Towards a quantitative assessment of neurodegeneration in Alzheimer's disease
Oleg Michailovich, Rinat Mukhometzianov
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that progressively destroys memory and other cognitive domains of the brain. While effective therapeutic mana…
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…
High-fidelity, accelerated whole-brain submillimeter in-vivo diffusion MRI using gSlider-Spherical Ridgelets (gSlider-SR)
Gabriel Ramos-Llordén, Lipeng Ning, Congyu Liao +4
Purpose: To develop an accelerated, robust, and accurate diffusion MRI acquisition and reconstruction technique for submillimeter whole human brain in-vivo scan on a clinical scann…
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…