THE AICON LAB
WHO WE ARE
The AI Collaborative Network (AICON) or Advanced Imaging and Computational Neuroimaging (AICON) Laboratory is at the forefront of integrating Artificial Intelligence (AI) into medical imaging.
Led by Professor Kyu Sung Choi, is a specialized research unit within the Radiology Department of Seoul National University Hospital.
Our mission is to redefine the landscape of neuroimaging by leveraging AI technologies.
Focused on enhancing the diagnosis, prognostication, and understanding of biological backgrounds, we aim to develop highly accurate and efficient AI models to be deployed in the real clinical practice.
Recent Research
Driven by physician-scientists and physician-investigators, the lab focuses on:
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
Methodologically, the lab specializes in:
Learning Disease Spatiotemporal Dynamics using Perfusion MRI.
Synthesizing and Validating Medical Imaging and Radiologic Reports with Generative Models.
Recent News
Congratulations! Our paper "Incorporating Supramaximal Resection into Survival Stratification of IDH-Wildtype Glioblastoma: A Refined Multi-institutional Recursive Partitioning Analysis" (https://aacrjournals.org/clincancerres/article-abstract/doi/10.1158/1078-0432.CCR-23-3845/745703/Incorporating-Supramaximal-Resection-into-Survival?redirectedFrom=fulltext) has been accepted to Clin Can Res (IF=11.5): Prof. Yae Won Park (leading co-first author) & Kyu Sung Choi
Congratulations! (Magna Cum Laude), Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM 2024): Junhyeok Lee, MS
Congratulations! (Magna Cum Laude), Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM 2024): Joon Jang, MS
Congratulations! Our paper "Comparative analysis of glymphatic system alterations in multiple sclerosis and neuromyelitis optica spectrum disorder using MRI indices from diffusion tensor imaging" (https://doi.org/10.1002/hbm.26680) has been accepted to Human Brain Mapping (IF=4.8): Prof. Minchul Kim
Congratulations! Our paper "Added Prognostic Value of 3D Deep Learning-Derived Features from Preoperative MRI for Adult-type Diffuse Gliomas" (https://pubmed.ncbi.nlm.nih.gov/37855826/) has been accepted to Neuro-Oncology (IF=15.9): Prof. Kyu Sung Choi
Congratulations! Best Oral Presentation Award (Silver Prize), annual conference of korean society of artificial intelligence in medicine (KOSAIM 2023): Junhyeok Lee, MS
"Continuous Spatio-Temporal Representation with Implicit Neural Representation and Neural Ordinary Differential Equation in Dynamic Susceptibility Contrast MRI"
Congratulations! Best Poster Presentation Award (Imaging I), annual conference of korean society of artificial intelligence in medicine (KOSAIM 2023): Junhyeok Lee, MS
"Improved Dynamic Contrast-Enhanced MRI for Diffuse Gliomas: Clinical Application of Deep Learning-Based Reconstruction and Denoising Techiques"
Congratulations! Contribution Award, The 11th International Congress on Magnetic Resonance Imaging & 28th Annual Scientific Meeting of KSMRM (ICMRI2023): Prof. Kyu Sung Choi
Congratulations! Best Trainee Scientific Awards Poster Presentation (GOLD), The 11th International Congress on Magnetic Resonance Imaging & 28th Annual Scientific Meeting of KSMRM (ICMRI2023): Junhyeok Lee, MS
"Continuous Spatio-Temporal Representation with Implicit Neural Representation and Neural Ordinary Differential Equation in Dynamic Susceptibility Contrast MRI"
Congratulations! Best Trainee Scientific Awards Oral Presentation (Silver), The 11th International Congress on Magnetic Resonance Imaging & 28th Annual Scientific Meeting of KSMRM (ICMRI2023): Joon Jang, MS
"Unsupervised Model-Free Leakage Detection in DCE-MRI Using Generative Adversarial Networks"
Congratulations! AICON lab has been introduced on BRIC : AI Collaborative Network (AICON) Laboratory
JOIN US
Preferred Skills
Research Topics : Deep Learning, MRI, Neuroimaging, Neuro-Oncology
Language : Python ( Pytorch, Tensorflow), R
For Perspective
SNUH Radiology AICON Lab will be accepting applications from highly motivated applicants, and you will get a extra point if you have preferred Skills.
Please email us here your CV if interested.