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New TetHeart framework reconstructs 4D heart mesh from sparse cardiac MRI

Researchers have developed TetHeart, a novel end-to-end framework for reconstructing 4D heart mesh from cardiac MRI sequences. This system can process both complete MRI stacks and sparse, real-time slice observations, making it applicable for both offline analysis and intra-procedural guidance. TetHeart utilizes deformable tetrahedra for shape and motion capture, an attentive slice-adaptive mechanism for integrating data from arbitrary slices, and a distillation strategy for accuracy under extreme sparsity. It requires minimal annotations, only at keyframes, and has demonstrated state-of-the-art accuracy and generalization across multiple datasets. AI

IMPACT Enables more accurate and flexible cardiac motion analysis, potentially improving diagnosis and interventional procedures.

RANK_REASON The cluster contains an academic paper detailing a new technical framework for medical imaging analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New TetHeart framework reconstructs 4D heart mesh from sparse cardiac MRI

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The cluster contains an academic paper detailing a new technical framework for medical imaging analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Yihong Chen, Jiancheng Yang, Deniz Sayin Mercadier, Hieu Le, Juerg Schwitter, Pascal Fua ·

    End-to-End 4D Heart Mesh Recovery Across Full-Stack and Sparse Cardiac MRI

    arXiv:2509.12090v3 Announce Type: replace Abstract: 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, limiting their applicability during intervention w…