Congratulations! Our paper "GlioSurv: Interpretable Transformer for Multimodal, Individualized Survival Prediction in Diffuse Glioma"  has been accepted to npj digital medicine (IF=15.1): Junhyeok Lee, MS

We are pleased to announce that Prof. Kyu Sung Choi has been invited to deliver a keynote lecture at the LIDM (Learning with Longitudinal Medical Images and Data) Workshop at MICCAI 2025. 

Congratulations! Our paper "ST-SRPerf: Continuous Spatiotemporal Representation for Perfusion MRI Super-resolution through Neural ODE and Implicit Neural Representation "  has been accepted to Computers in Biology and Medicine (IF=6.3; JCR top 5%): Junhyeok Lee, MS

Congratulations! Our abstract "Exploring evidence for vertical recurrence of glioblastoma using dynamic contrast-enhanced MRI" has been accepted to Annual Meeting of Radiological Society of North America 2025 (RSNA 2025): Prof. Minchul Kim, MD, PhD (Collaborator) 

Congratulations! Our abstract "Lesion-Aware Post-Training of Latent Diffusion Models for Synthesizing Diffusion MRI from CT Perfusion " has been provisionally accepted (Top 9%) to International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2025): Junhyeok Lee, MS 

Congratulations! New Researcher Academic Award, Korean Society of Neuroradiology (KSNR2025): Prof. Kyu Sung Choi

Congratulations! Our paper "Association of Deep Learning-Based Chest CT-Derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis"  has been accepted to Radiology (IF=12.1): Prof. Kyu Sung Choi 

Congratulations! Our paper "Unsupervised Deep Learning for Model-Free Blood‒Brain Barrier Leakage Detection with Dynamic Contrast-Enhanced MRI in Diffuse Gliomas"  has been accepted to Radiology: Artificial Intelligence (IF=8.1): Joon Jang, MS 

Driven by physician-scientists and physician-investigators, the lab focuses on:

1. Disease-wisely:

• Brain Glymphatics Analysis via perfusion MRI for neurodegeneration, demyelinating disease, and Glioblastoma.

• Tumor Microenvironment Analysis using multiparametric MRI in Glioblastoma.

• Longitudinal Volumetric Change Analysis in Degenerative, Demyelinating Diseases, and Autoimmune Encephalitis.

• Prediction and Generative models in Stroke using Brain CT

2. Methodologically, the lab specializes in:

• Learning Disease Spatiotemporal Dynamics using Perfusion MRI.

• Synthesizing and Validating Medical Imaging and Radiologic Reports with Generative Models.