5 papers
MedLayBench-V: A Large-Scale Benchmark for Expert-Lay Semantic Alignment in Medical Vision Language Models
Han Jang, Junhyeok Lee, Heeseong Eum +1
Medical Vision-Language Models (Med-VLMs) have achieved expert-level proficiency in interpreting diagnostic imaging. However, current models are predominantly trained on profession…
Evidential Perfusion Physics-Informed Neural Networks with Residual Uncertainty Quantification
Junhyeok Lee, Minseo Choi, Han Jang +5
Physics-informed neural networks (PINNs) have shown promise in addressing the ill-posed deconvolution problem in computed tomography perfusion (CTP) imaging for acute ischemic stro…
MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models
Han Jang, Junhyeok Lee, Songsoo Kim +4
Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains underexplored. With the 21s…
Hierarchical Perfusion Graphs for Tumor Heterogeneity Modeling in Glioma Molecular Subtyping
Han Jang, Junhyeok Lee, Heeseong Eum +4
Precise molecular subtyping of gliomas, including isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion, directly guides surgical and therapeutic decisions, yet currently r…
Segmentation-before-Staining Improves Structural Fidelity in Virtual IHC-to-Multiplex IF Translation
Junhyeok Lee, Han Jang, Heeseong Eum +2
Multiplex immunofluorescence (mIF) enables simultaneous single-cell quantification of multiple biomarkers within intact tissue architecture, yet its high reagent cost, multi-round…