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ARXIV:2605.13994 · MEDICAL AI · SUBMITTED 15 MAY · 20:13 UTC · FRESHNESS FRESH
ARXIV:2605.13994MEDICAL AISUBMITTED 15 MAY · 20:13 UTCFRESHNESS FRESHXiaoyue Liu · Xiaohan Yuan · Mark Y Chan · Ching-Hui Sia · Lei Li · arXiv
An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment.
Opportunity summary
Pain An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment.
Evidence 0 refs | 0 sources | 0% coverage
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An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by…
Accurate 3D+t whole-heart mesh reconstruction from cine MRI is a clinically crucial yet technically challenging task. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by…
ScienceToStartup currently rates this 5.0/10 on the public viability pass. Specifically, we introduce a differentiable rendering loss that enables supervision of 3D+t whole-heart mesh from multi-view sparse contours of cine MRI.
Medical AI moved forward this cycle; last verified May 2026. Public score 5.0/10.
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An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment.
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10.48550/arXiv.2605.13994An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment.
Abstract
Accurate 3D+t whole-heart mesh reconstruction from cine MRI is a clinically crucial yet technically challenging task. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by 2D image slices and the tight coupling between cardiac shape and motion. Current cardiac image-to-mesh approaches typically reconstruct only a subset of cardiac chambers or a single phase of the cardiac cycle. In this work, we propose CineMesh4D, a novel end-to-end 4D (3D+t) pipeline that directly reconstructs patient-specific whole-heart mesh from multi-view 2D cine MRI via cross-domain mapping. Specifically, we introduce a differentiable rendering loss that enables supervision of 3D+t whole-heart mesh from multi-view sparse contours of cine MRI. Furthermore, we develop a dual-context temporal block that fuses global and local cardiac temporal information to capture high-dimensional sequential patterns. In quantitative and qualitative evaluations, CineMesh4D outperforms existing approaches in terms of reconstruction quality and motion consistency, providing a practical pathway for personalized real-time cardiac assessment. The code will be publicly released once the manuscript is accepted.
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PROBLEM
An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by 2D image slices and the tight coupling...
METHOD
Accurate 3D+t whole-heart mesh reconstruction from cine MRI is a clinically crucial yet technically challenging task. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by 2D image slices and the tight coupling between c...
RESULT
ScienceToStartup currently rates this 5.0/10 on the public viability pass. Specifically, we introduce a differentiable rendering loss that enables supervision of 3D+t whole-heart mesh from multi-view sparse contours of cine MRI.
WHY NOW
Medical AI moved forward this cycle; last verified May 2026. Public score 5.0/10.
Abstract-backed public claims while anchored extraction refreshes.
An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by 2D image slices and the tight coupling between cardiac shape and motion.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Accurate 3D+t whole-heart mesh reconstruction from cine MRI is a clinically crucial yet technically challenging task. The difficulty of this task arises from two coupled factors: inherently sparse sampling of 3D cardiac anatomy by 2D image slices and the tight coupling between cardiac shape and motion.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 5.0/10 on the public viability pass. Specifically, we introduce a differentiable rendering loss that enables supervision of 3D+t whole-heart mesh from multi-view sparse contours of cine MRI.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Medical AI moved forward this cycle; last verified May 2026. Public score 5.0/10.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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An end-to-end pipeline for personalized 4D whole-heart mesh reconstruction from sparse cine MRI, improving cardiac assessment.
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