25 citations · 72 across the 16 of their papers we have counts for
16 papers
IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data
Noga Kertes, Yael Zaffrani-Reznikov, Onur Afacan +3
Quantitative analysis of pseudo-diffusion in diffusion-weighted magnetic resonance imaging (DWI) data shows potential for assessing fetal lung maturation and generating valuable im…
PCMC-T1: Free-breathing myocardial T1 mapping with Physically-Constrained Motion Correction
Eyal Hanania, Ilya Volovik, Lilach Barkat +2
T1 mapping is a quantitative magnetic resonance imaging (qMRI) technique that has emerged as a valuable tool in the diagnosis of diffuse myocardial diseases. However, prevailing ap…
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…