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cs.CV2026

TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIs

Junhyeok Lee, Kyu Sung Choi

Reconstructing diffusion tensors from sparse DWIs is critical for accelerating Diffusion Tensor Imaging (DTI) in clinical settings, yet current deep learning approaches frequently…

cs.CV2026

Spatio-Temporal Mixture-of-Modality-Experts Diffusion for Quantitative DCE-MRI Synthesis from Incomplete MR Sequences

Junhyeok Lee, Kyu Sung Choi

Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risks and protocol variability. Pr…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…