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Supporting transformer-based cardiac MRI segmentation with text-to-image controllable diffusion pipelines
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DOI：10.1016/j.compmedimag.2026.102803.png)
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Abstract
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• Generation of realistic cardiac MRI images with their semantic labels. • Image realism quality assessed using well known distribution metrics. • Synthetic data used to augment train set of Segformer to cardiac regions. • Evaluation of model performance using real, synthetic, and mixed train sets.
Keywords:
Cardiac diseases
Generative artificial intelligence
Cardiac MRI
Diffusion models
Segmentation
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