Medical Imaging &
Computer Vision Lab
Department of Artificial Intelligence
School of Computing
2023.8. Accepted to Medical Image Analysis. Congrats to Mahbaneh!
2023.3. Dayun Ju and Chanyoung Kim join our lab!
2023.2. Accepted for Machine Learning on theoretical domain generalization. Congrats to Anthony!
2023.1. Accepted for ISBI 2023.
2023.1. Gayoon Choi, Taejin Jeong, and Jeahoon Joo join our lab!
2022.7. Yumin Kim, Seil Kang, Kyobin Choo, Hyunjin Kim, and Donghyun Kim join our lab!
2022.5. Accepted for UAI 2022, Eindhoven, the Netherlands for an Oral Presentation. Congrats to Anthony!
2022.4. Accepted for IJCAI 2022, Vienna. Congrats to Xingchen and Anthony!
2022.3. Yujin Yang and Woojung Han join our lab!
2022.3. Accepted for Findings of ACL 2022. Congrats to Anthony!
2022.3. Joining as an Assistant Professor in the Department of Artificial Intelligence at Yonsei University
2021.10. Accepted for NeuroImage. Congrats to Mahbaneh!
2021.8. Accepted for The First Workshop on Computer Vision for Automated Medical Diagnosis @ ICCV 2021. Congrats to Mahbaneh!
2021.6. Accepted for MICCAI 2021, Virtual. Congrats to Anthony!
2021.3. Accepted for AAIC 2021, Denver, USA. Congrats to Mahbaneh!
2021.5. Accepted for MIDL 2021, Virtual. Congrats to Shibo!
2021.2. Accepted for IPMI 2021, Virtual.
2021.2. Two Full Papers Accepted for ISBI 2021, Virtual. Congrats to Anthony and Xingchen!
2020.12. Received Alzheimer's Disease Research Center Developmental Project grant by Pitt ADRC for 2021-2022 on "A bias-resilient deep learning algorithm for robust white matter hyperintensity segmentation on Alzheimer’s disease data with confounding factors"
2020.10. Accepted for The Anatomical Record.
2020.7. Accepted for an Oral Presentation at The Workshop on BioImage Computing @ ECCV 2020.
Medical Imaging & Computer Vision (MICV) Lab tackles an array of problems in
Medical imaging analysis
Alzheimer's disease analysis with MRI/PET/DTI
brain lesion segmentation
Computer vision / Machine learning / Deep learning
PAC-Bayesian performance guarantee
domain generalization/adaptation - theory and application