8 papers
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…
Atlas-Assisted Segment Anything Model for Fetal Brain MRI (FeTal-SAM)
Qi Zeng, Weide Liu, Bo Li +3
This paper presents FeTal-SAM, a novel adaptation of the Segment Anything Model (SAM) tailored for fetal brain MRI segmentation. Traditional deep learning methods often require lar…
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…
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…
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…
Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge
Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67
Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…