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cs.CV2026

Whole-Body MRI Classification via Prompt-Based Clinical Conditioning

Laura Daza, Marta Hasny, Cristina González +1

Combining whole-body magnetic resonance imaging (WB-MRI) with clinical variables has the potential to improve systemic disease diagnosis by leveraging complementary sources of pati…

cs.CV2025

No Data? No Problem: Robust Vision-Tabular Learning with Missing Values

Marta Hasny, Laura Daza, Keno Bressem +2

Large-scale medical biobanks provide imaging data complemented by extensive tabular information, such as clinical measurements or demographics. However, this abundance of tabular a…

cs.CV2025

Semantic Alignment of Unimodal Medical Text and Vision Representations

Maxime Di Folco, Emily Chan, Marta Hasny +2

General-purpose AI models, particularly those designed for text and vision, demonstrate impressive versatility across a wide range of deep-learning tasks. However, they often under…

cs.CV2025

Tables Guide Vision: Learning to See the Heart through Tabular Data

Marta Hasny, Maxime Di Folco, Keno Bressem +1

Contrastive learning methods in computer vision typically rely on augmented views of the same image or multimodal pretraining strategies that align paired modalities. However, thes…

cs.CV2024

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis

Yousef Yeganeh, Azade Farshad, Ioannis Charisiadis +5

Scaling by training on large datasets has been shown to enhance the quality and fidelity of image generation and manipulation with diffusion models; however, such large datasets ar…