6 citations · 10 across the 8 of their papers we have counts for
4 papers · 1 filter
Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging
Haoxu Huang, Long Chen, Jingyun Chen +8
Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic and fluid-sensitive T2-weighted (T…
NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding
Mohammad H. Abbasi, Favour Nerrise, Shaurnav Ghosh +12
We present NeuroQA, a large-scale benchmark for visual question answering in 3D brain magnetic resonance imaging (MRI), with 56,953 QA pairs from 12,977 subjects across 12 datasets…
CheXTemporal: A Dataset for Temporally-Grounded Reasoning in Chest Radiography
Eva Prakash, Yunhe Gao, Chong Wang +10
Chest radiograph interpretation requires temporal reasoning over prior and current studies, yet most vision-language models are trained on static image-report pairs and lack explic…
A Reasoning-Enabled Vision-Language Foundation Model for Chest X-ray Interpretation
Yabin Zhang, Chong Wang, Yunhe Gao +19
Chest X-rays (CXRs) are among the most frequently performed imaging examinations worldwide, yet rising imaging volumes increase radiologist workload and the risk of diagnostic erro…