3 papers
cs.CV2026
Metadata-Aware Adaptation of a Generative Foundation Model for Conditional CMR Synthesis
Marc Rodríguez, Grzegorz Skorupko, Nay Aung +3
Synthetic image generation is a promising strategy to address data scarcity and the underrepresentation of clinically important phenotypes in medical imaging, yet generating images…
eess.IV2025
SAGCNet: Spatial-Aware Graph Completion Network for Missing Slice Imputation in Population CMR Imaging
Junkai Liu, Nay Aung, Theodoros N. Arvanitis +4
Magnetic resonance imaging (MRI) provides detailed soft-tissue characteristics that assist in disease diagnosis and screening. However, the accuracy of clinical practice is often h…
cs.CV2025
RefineSeg: Dual Coarse-to-Fine Learning for Medical Image Segmentation
Anghong Du, Nay Aung, Theodoros N. Arvanitis +4
High-quality pixel-level annotations of medical images are essential for supervised segmentation tasks, but obtaining such annotations is costly and requires medical expertise. To…