25 citations · 72 across the 16 of their papers we have counts for
8 papers · 1 filter
P2T2: a Physically-primed deep-neural-network approach for robust distribution estimation from quantitative -weighted MRI
Hadas Ben-Atya, Moti Freiman
Estimating relaxation time distributions from multi-echo -weighted MRI () data can provide valuable biomarkers for assessing inflammation, demyelination, edema, an…
MA-RECON: Mask-aware deep-neural-network for robust fast MRI k-space interpolation
Nitzan Avidan, Moti Freiman
High-quality reconstruction of MRI images from under-sampled `k-space' data, which is in the Fourier domain, is crucial for shortening MRI acquisition times and ensuring superior t…
qDWI-Morph: Motion-compensated quantitative Diffusion-Weighted MRI analysis for fetal lung maturity assessment
Yael Zaffrani-Reznikov, Onur Afacan, Sila Kurugol +2
Quantitative analysis of fetal lung Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging biomarkers that indirectly reflect fetal lung maturation. Ho…
NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data
Samah Khawaled, Moti Freiman
Uncertainty quantification in deep-learning (DL) based image reconstruction models is critical for reliable clinical decision making based on the reconstructed images. We introduce…
PVBM: A Python Vasculature Biomarker Toolbox Based On Retinal Blood Vessel Segmentation
Jonathan Fhima, Jan Van Eijgen, Ingeborg Stalmans +3
Introduction: Blood vessels can be non-invasively visualized from a digital fundus image (DFI). Several studies have shown an association between cardiovascular risk and vascular f…
SUPER-IVIM-DC: Intra-voxel incoherent motion based Fetal lung maturity assessment from limited DWI data using supervised learning coupled with data-consistency
Noam Korngut, Elad Rotman, Onur Afacan +5
Intra-voxel incoherent motion (IVIM) analysis of fetal lungs Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging bio-markers that reflect, indirectl…