9 papers
End-to-End 4D Heart Mesh Recovery Across Full-Stack and Sparse Cardiac MRI
Yihong Chen, Jiancheng Yang, Deniz Sayin Mercadier +3
Reconstructing cardiac motion from CMR sequences is critical for diagnosis, prognosis, and intervention. Existing methods rely on complete CMR stacks to infer full heart motion, li…
GenMed: A Pairwise Generative Reformulation of Medical Diagnostic Tasks
Hantao Zhang, Weidong Guo, Yuhe Liu +5
Data-driven medical AI is traditionally formulated as a discriminative mapping from input to output via a learned function , which does not generalize well across hetero…
Refining 3D Medical Segmentation with Verbal Instruction
Kangxian Xie, Jiancheng Yang, Nandor Pinter +3
Accurate 3D anatomical segmentation is essential for clinical diagnosis and surgical planning. However, automated models frequently generate suboptimal shape predictions due to fac…
EyeWorld: A Generative World Model of Ocular State and Dynamics
Ziyu Gao, Xinyuan Wu, Xiaolan Chen +10
Ophthalmic decision-making depends on subtle lesion-scale cues interpreted across multimodal imaging and over time, yet most medical foundation models remain static and degrade und…
PrIntMesh: Precise Intersection Surfaces for 3D Organ Mesh Reconstruction
Deniz Sayin Mercadier, Hieu Le, Yihong Chen +3
Human organs are composed of interconnected substructures whose geometry and spatial relationships constrain one another. Yet, most deep-learning approaches treat these parts indep…
DiffAtlas: GenAI-fying Atlas Segmentation via Image-Mask Diffusion
Hantao Zhang, Yuhe Liu, Jiancheng Yang +3
Accurate medical image segmentation is crucial for precise anatomical delineation. Deep learning models like U-Net have shown great success but depend heavily on large datasets and…