3 papers
cs.CV2026
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
AI-based association analysis for medical imaging using latent-space geometric confounder correction
Xianjing Liu, Bo Li, Meike W. Vernooij +3
This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves…
eess.IV2025
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…