5 papers · 1 filter
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…
Domain-Specialized Interactive Segmentation Framework for Meningioma Radiotherapy Planning
Junhyeok Lee, Han Jang, Kyu Sung Choi
Precise delineation of meningiomas is crucial for effective radiotherapy (RT) planning, directly influencing treatment efficacy and preservation of adjacent healthy tissues. While…