Hamza Kebiri

A-eye: Automated 3D MRI Segmentation and Morphometric Feature Extraction for Eye and Orbit Atlas Construction

This study introduces an automated 3D MRI segmentation method for the human eye and orbit, providing large-scale unbiased atlases for clinical research.

Domain shifts in infant brain diffusion MRI: Quantification and mitigation for fODF estimation

This study evaluates deep learning models for fODF estimation in infant brain MRI, finding that U-Net performs best with fewer gradient directions, while MLP and Transformer improve with more directions.

Functional organization of the neonatal thalamus across development depicted by functional MRI

The paper uses functional MRI data to study thalamic functional organization in newborns, identifying age-related changes and specific thalamic units.

Deep learning microstructure estimation of developing brains from diffusion MRI: a newborn and fetal study

This study uses deep learning to estimate fiber orientation distribution functions (FODs) from limited diffusion MRI data in newborns and fetuses, achieving results comparable to standard methods with fewer measurements.

Through-plane super-resolution with autoencoders in diffusion magnetic resonance imaging of the developing human brain

This paper uses an autoencoder to enhance through-plane resolution in fetal brain diffusion MRI, outperforming interpolation methods on pre-term newborn data.