6 papers · 1 filter
Inference-Time Dynamic Modality Selection for Incomplete Multimodal Classification
Siyi Du, Xinzhe Luo, Declan P. O'Regan +1
Multimodal deep learning (MDL) has achieved remarkable success across various domains, yet its practical deployment is often hindered by incomplete multimodal data. Existing incomp…
Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM
Jingxuan Kang, Ziqi Zhang, Shaoming Zheng +9
Segmentation is central to clinical diagnosis and monitoring, yet the reliability of modern foundation models in medical imaging still depends on the availability of precise prompt…
Adaptive Conditional Contrast-Agnostic Deformable Image Registration with Uncertainty Estimation
Yinsong Wang, Xinzhe Luo, Siyi Du +1
Deformable multi-contrast image registration is a challenging yet crucial task due to the complex, non-linear intensity relationships across different imaging contrasts. Convention…
STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal Classification
Siyi Du, Xinzhe Luo, Declan P. O'Regan +1
Multimodal image-tabular learning is gaining attention, yet it faces challenges due to limited labeled data. While earlier work has applied self-supervised learning (SSL) to unlabe…
CAR: Contrast-Agnostic Deformable Medical Image Registration with Contrast-Invariant Latent Regularization
Yinsong Wang, Siyi Du, Shaoming Zheng +2
Multi-contrast image registration is a challenging task due to the complex intensity relationships between different imaging contrasts. Conventional image registration methods are…
TIP: Tabular-Image Pre-training for Multimodal Classification with Incomplete Data
Siyi Du, Shaoming Zheng, Yinsong Wang +3
Images and structured tables are essential parts of real-world databases. Though tabular-image representation learning is promising to create new insights, it remains a challenging…