Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography
Myocardial infarction (MI) remains a leading cause of mortality worldwide. Echocardiography (Echo) is a widely available modality for MI assessment, where regional wall motion abnormality is a key indicator. Prior learning based methods for myocardial motion analysis often use handcrafted descriptors or densely supervised estimation, but the need for extensive annotation limits applicability. Foundation models have recently improved vision-based Echo analysis; however, most methods operate on single views and segment-level localization remains unreliable under view-dependent ambiguity, especia
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- LinkedLinked via arxiv author · 85%Guang Yang →
“Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography”
- LinkedLinked via arxiv author · 85%Wentian Xu →
“Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography”
- LinkedLinked via arxiv author · 85%Siyu Wang →
“Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography”
- LinkedLinked via arxiv author · 85%Betty Raman →
“Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography”
- LinkedLinked via arxiv author · 85%Lei Li →
“Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography”
- LinkedLinked via arxiv author · 85%Vicente Grau →
“Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography”