4 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.CV2026★ 2 cited
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…
cs.CV2025★ 4 cited
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…
eess.IV2025★ 3 cited
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…