RePCM: Region-Specific and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis
Xuan Yang, Xiaohan Yuan, Hao Li, Lingyu Chen, Yanan Liu, and Lei Li

TL;DR
RePCM is a novel method for synthesizing full cardiac motion sequences from a single end-diastolic frame, capturing regional and disease-specific dynamics more accurately than traditional global models.
Contribution
The paper introduces a region-aware, phenotype-adaptive bi-ventricular motion synthesis framework that explicitly models regional differences and disease variability.
Findings
Consistent improvements in geometric and functional metrics across datasets.
Enhanced preservation of region-specific cardiac dynamics.
Effective modeling of inter-disease variability in cardiac motion.
Abstract
Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally dense mesh sequences are difficult to obtain in practice, we focus on leveraging the more accessible end-diastolic frame to infer a full-cycle sequence. Due to strong regional and disease-specific differences, traditional methods often oversmooth the data by relying on generative models that are optimized for global patterns. To address this problem, we propose Region-Aware and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis (RePCM) for single frame Bi-ventricular mesh motion completion. In Stage I, a reconstruction network learns vertex wise motion descriptors and clustering yields a data driven functional partition, providing an explicit motion derived region structure. In Stage II, a Region-Specific Injection Module enforces…
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