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Demonstrates a simulation pipeline generating cine DENSE images with ground-truth strain, facilitating deep-learning validation for clinical cardiovascular MRI.
Generating realistic cine DENSE images with high-resolution ground-truth strain and myocardial segmentation enables accurate evaluation of strain analysis tools, while reproducing key in-vivo acquisition features, and will facilitate the future development of deep-learning models for myocardial strain analysis, enhancing clinical CMR workflows.
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Barbaroux et al. (2025) studied this question.
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