4 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…
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…
Lesion-Aware Post-Training of Latent Diffusion Models for Synthesizing Diffusion MRI from CT Perfusion
Junhyeok Lee, Hyunwoong Kim, Hyungjin Chung +4
Image-to-Image translation models can help mitigate various challenges inherent to medical image acquisition. Latent diffusion models (LDMs) leverage efficient learning in compress…