4 papers
Location-Aware Fine-Grained Representation Learning for Medical Vision Foundation Models
Myeongkyun Kang, Yanting Yang, Xiaoxiao Li
Fine-grained visual representations are essential for medical image analysis, particularly when diagnostically relevant evidence is subtle and spatially localized. Modern transform…
UltraVR: A Diagnostic Ultra-Resolution Image-VQA Benchmark for Evidence-Grounded Reasoning
Gexin Huang, Yanting Yang, Myeongkyun Kang +6
Vision-language models (VLMs) excel on visual question answering and multimodal reasoning benchmarks. Yet their capability on ultra-resolution images - where critical evidence is t…
LoFi: Location-Aware Fine-Grained Representation Learning for Chest X-ray
Myeongkyun Kang, Yanting Yang, Xiaoxiao Li
Fine-grained representation learning is crucial for retrieval and phrase grounding in chest X-rays, where clinically relevant findings are often spatially confined. However, the la…
NeuroLIP: Interpretable and Fair Cross-Modal Alignment of fMRI and Phenotypic Text
Yanting Yang, Xiaoxiao Li
Integrating functional magnetic resonance imaging (fMRI) connectivity data with phenotypic textual descriptors (e.g., disease label, demographic data) holds significant potential t…