From the 1 of 5 linked papers with an AI index.
5 papers
INFANiTE: Implicit Neural representation for high-resolution Fetal brain spatio-temporal Atlas learNing from clinical Thick-slicE MRI
Xiaotian Hu, Mingxuan Liu, Hongjia Yang +10
The paper introduces INFANiTE, an implicit neural representation framework that builds high‑resolution spatio‑temporal fetal brain atlases directly from thick‑slice MRI, eliminatin…
Annotation-free deep learning for detection and segmentation of fetal germinal matrix-intraventricular hemorrhage in brain MRI
Mingxuan Liu, Yingqi Hao, Yi Liao +17
Prenatal germinal matrix-intraventricular hemorrhage (GMH-IVH) is a leading cause of infant mortality and neurodevelopmental impairment, yet its manual diagnosis and lesion segment…
A physics-informed foundation model for quantitative diffusion MRI
Zihan Li, Jialan Zheng, Ziyu Li +18
Understanding the human brain requires access to its microscopic tissue architecture. Diffusion magnetic resonance imaging (MRI) provides the only noninvasive window into whole-bra…
Towards Reliable Fetal Ultrasound Interpretation with Multi-Agent Collaboration
Xiaotian Hu, Mingxuan Liu, Junwei Huang +13
Automated fetal ultrasound interpretation requires a workflow from visual perception, including plane recognition and anatomical segmentation, to clinical understanding, including…
EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT
Xuguang Bai, Mingxuan Liu, Tongxi Song +6
Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imaging increasingly exceed what c…