3 papers
cs.CV2026
Metadata Supervised MRI Representations for Modelling and Controlling Acquisition Variability
Mehmet Yigit Avci, Pedro Borges, Virginia Fernandez +5
Magnetic resonance imaging exhibits substantial acquisition variability, where identical anatomy can appear markedly different across scanners and imaging protocols. Consequently,…
cs.CV2025
DIST-CLIP: Arbitrary Metadata and Image Guided MRI Harmonization via Disentangled Anatomy-Contrast Representations
Mehmet Yigit Avci, Pedro Borges, Virginia Fernandez +4
Deep learning holds immense promise for transforming medical image analysis, yet its clinical generalization remains profoundly limited. A major barrier is data heterogeneity. This…
cs.CV2025
Metadata-Aligned 3D MRI Representations for Contrast Understanding and Quality Control
Mehmet Yigit Avci, Pedro Borges, Virginia Fernandez +4
Magnetic Resonance Imaging suffers from substantial data heterogeneity and the absence of standardized contrast labels across scanners, protocols, and institutions, which severely…