welcome
Welcome to Medical Imaging and Intelligent Reality Lab.
MI2RL is a part of Asan Medical Center, a UUCM-affiliated leading hospital in South Korea,
and University of Ulsan College of Medicine.
Our lab belongs to the Department of Convergence Medicine and Radiology.
MI2RL's research interests are the areas of image-based clinical applications, such as artificial intelligence, 3D printing, medical image processing, computer-aided surgery, robotic interventions, etc. for translational researches in hospitals.
Our lab works closely with multiple clinical collaborators from AMC, and our goal is to use novel technology to provide better treatment for patients (with cancer, oncological, pulmonological, cardiological, neurological, etc. diseases).
Research Fields
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Medical imaging with deep learning, 3D printing in medicine, image guided robotics, computer aided surgery,
flows in human body, medical image processing; lung, brain, heart, liver, breast, dental. Practical consideration for deep learning application in medicine. -
Efficient labeling technology, interpretability and visualization (no blackbox), uncertainty (data level, decision level), reproducibility of deep learning, novelty in supervised learning, one-shot or multi-shot learning due to Imbalanced data set or rare disease, deep survival, physics induced machine learning.
research highlights
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Latest lecture
![[2024.05.02] Pose Anything: A Graph-Based Approach for Category-Agnostic Pose Estimation, 발표 : 김영제](https://i.ytimg.com/vi/rks_FD-T66M/mqdefault.jpg 1x, https://i.ytimg.com/vi/rks_FD-T66M/maxresdefault.jpg 2x)
![[2024.03.07] 공학딥러닝 - Finetuned Language Models Are Zero-Shot Learners, 발표 : 김태원](https://i.ytimg.com/vi/ytHGq1e3EAk/mqdefault.jpg 1x, https://i.ytimg.com/vi/ytHGq1e3EAk/maxresdefault.jpg 2x)
![[2024.04.18] 공학딥러닝 - High-Resolution Image Synthesis with Latent Diffusion Models, 발표 : 박창현](https://i.ytimg.com/vi/u-TjiSBfEZU/mqdefault.jpg 1x, https://i.ytimg.com/vi/u-TjiSBfEZU/maxresdefault.jpg 2x)
![[2024.02.29] MI2RL 랩미팅 멀티모달팀 - Medical Multimodal Survey (경성구 발표)](https://i.ytimg.com/vi/ZfBa0zKS9MA/mqdefault.jpg 1x, https://i.ytimg.com/vi/ZfBa0zKS9MA/maxresdefault.jpg 2x)
![[2024.02.22]공학딥러닝 논문리뷰 Disruptive Autoencoders: Leveraging Low-level features for 3D MI Pre-training](https://i.ytimg.com/vi/jgGncLfDXFs/mqdefault.jpg 1x, https://i.ytimg.com/vi/jgGncLfDXFs/maxresdefault.jpg 2x)
![[MI2RL연구개론] 39. Vision of Digital Healthcare](https://i.ytimg.com/vi/1ztBXuHieHQ/mqdefault.jpg 1x, https://i.ytimg.com/vi/1ztBXuHieHQ/maxresdefault.jpg 2x)
![[MI2RL연구개론] 38. Retentive Network: A Successor to Transformer for Large Language Model](https://i.ytimg.com/vi/lSZouMCFgfI/mqdefault.jpg 1x, https://i.ytimg.com/vi/lSZouMCFgfI/maxresdefault.jpg 2x)
![[MI2RL연구개론]37. Dive into Deep Learning](https://i.ytimg.com/vi/2REUuEATYJo/mqdefault.jpg 1x, https://i.ytimg.com/vi/2REUuEATYJo/maxresdefault.jpg 2x)