collaborators

5 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…

cs.CV2026

Chain of Flow: ECG-Conditioned 4D Cardiac Cine Generation from Patient-Specific Anatomical Anchor

Haofan Wu, Nay Aung, Theodoros N. Arvanitis +3

Cardiac cine magnetic resonance imaging (MRI) is central to functional cardiac assessment, yet a full current cine sequence may not always be directly available at the point of ana…

eess.IV2026

Exploiting Completeness Perception with Diffusion Transformer for Unified 3D MRI Synthesis

Junkai Liu, Nay Aung, Theodoros N. Arvanitis +3

Missing data problems, such as missing modalities in multi-modal brain MRI and missing slices in cardiac MRI, pose significant challenges in clinical practice. Existing methods rel…

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…