8 citations · 28 across the 16 of their papers we have counts for
10 papers · 1 filter
AWR-Net: Decoupling Anatomy and Appearance for 3D Fetal Brain Ultrasound Synthesis
Yuhuan Lu, Sergio Valencia, Yuanji Zhang +4
Three-dimensional fetal brain ultrasound offers non-ionizing, cost-effective imaging with rich spatial information for comprehensive anatomical assessment, yet its development rema…
Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening
Yuhao Huang, Yuanji Zhang, Yuhuan Lu +3
Assessment of ventriculomegaly (VM) on fetal brain ultrasound relies primarily on measuring lateral ventricular atrial width on standard planes, which is operator-dependent and may…
USFetal: Tools for Fetal Brain Ultrasound Compounding
Mohammad Khateri, Morteza Ghahremani, Sergio Valencia +5
Ultrasound offers a safe, cost-effective, and widely accessible technology for fetal brain imaging, making it especially suitable for routine clinical use. However, it suffers from…
MRI Super-Resolution with Deep Learning: A Comprehensive Survey
Mohammad Khateri, Serge Vasylechko, Morteza Ghahremani +9
High-resolution (HR) magnetic resonance imaging (MRI) is crucial for many clinical and research applications. However, achieving it remains costly and constrained by technical trad…
FetDTIAlign: A Deep Learning Framework for Affine and Deformable Registration of Fetal Brain dMRI
Bo Li, Qi Zeng, Simon K. Warfield +1
Diffusion MRI (dMRI) provides unique insights into fetal brain microstructure in utero. Longitudinal and cross-sectional fetal dMRI studies can reveal crucial neurodevelopmental ch…
Detailed delineation of the fetal brain in diffusion MRI via multi-task learning
Davood Karimi, Camilo Calixto, Haykel Snoussi +6
Diffusion-weighted MRI is increasingly used to study the normal and abnormal development of fetal brain in-utero. Recent studies have shown that dMRI can offer invaluable insights…
Ground-truth effects in learning-based fiber orientation distribution estimation in neonatal brains
Rizhong Lin, Hamza Kebiri, Ali Gholipour +4
Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive method for depicting brain microstructure in vivo. Fiber orientation distributions (FODs) are mathematical representat…
Diffusion MRI with Machine Learning
Davood Karimi, Simon K. Warfield
\hspace{2mm} Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural conn…
Cross-Age and Cross-Site Domain Shift Impacts on Deep Learning-Based White Matter Fiber Estimation in Newborn and Baby Brains
Rizhong Lin, Ali Gholipour, Jean-Philippe Thiran +3
Deep learning models have shown great promise in estimating tissue microstructure from limited diffusion magnetic resonance imaging data. However, these models face domain shift ch…
Fetal-BET: Brain Extraction Tool for Fetal MRI
Razieh Faghihpirayesh, Davood Karimi, Deniz Erdoğmuş +1
Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. However, it has been a very challenging task due to non-standard fetal head pose,…