3 papers
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…
cs.CV2025
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…
cs.CV2024
Improving Factuality of 3D Brain MRI Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation
Junhyeok Lee, Yujin Oh, Dahyoun Lee +9
Acute ischemic stroke (AIS) requires time-critical decision-making, where inaccurate interpretation of neuroimaging findings can lead to irreversible disability. Diffusion-weighted…