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Cardiac Mesh Flow: One-Step Generation of 3D+t Cardiac Four-Chamber Meshes via Flow Matching
Qiang Ma, Qingjie Meng, Mengyun Qiao +3
Spatio-temporal (3D+t) generative modelling of cardiac shape and motion is crucial for understanding heart structure and function at population scale. Existing generative models fo…
Learning a dynamic four-chamber shape model of the human heart for 95,695 UK Biobank participants
Qiang Ma, Qingjie Meng, Yicheng Wu +6
The human heart is a sophisticated system composed of four cardiac chambers with distinct shapes, which function in a coordinated manner. Existing shape models of the heart mainly…
CardiacFlow: 3D+t Four-Chamber Cardiac Shape Completion and Generation via Flow Matching
Qiang Ma, Qingjie Meng, Mengyun Qiao +3
Learning 3D+t shape completion and generation from multi-view cardiac magnetic resonance (CMR) images requires a large amount of high-resolution 3D whole-heart segmentations (WHS)…
SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints
Berke Doga Basaran, Xinru Zhang, Paul M. Matthews +1
Assessment of lesions and their longitudinal progression from brain magnetic resonance (MR) images plays a crucial role in diagnosing and monitoring multiple sclerosis (MS). Machin…
A Foundation Model for Brain Lesion Segmentation with Mixture of Modality Experts
Xinru Zhang, Ni Ou, Berke Doga Basaran +8
Brain lesion segmentation plays an essential role in neurological research and diagnosis. As brain lesions can be caused by various pathological alterations, different types of bra…