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방사선 및 의료 지능 연구실은 의료, 방사선, 원자력에 기반 지식을 바탕으로 인공지능 기술을 접목한 다양한 연구를 수행하고 있습니다. 주로 의료영상에 컴퓨터 비전 기술을 적용하고 있으며, 컴퓨터 단층영상에서의 인공음영 제거 기술 개발, 주요 장기 자동분할 기술 개발 등 임상에 실질적으로 도움이 되는 기술 개발을 목표로 합니다. 이를 위하여 서울대학교, 서울대학교병원 영상의학과, 삼성서울병원 방사선종양학과 등과 공동 연구를 진행하고 있습니다.
Radiation & Medical Intelligence Lab (RAMI Lab) has conducted various research applying artificial intelligence (AI) technology into medical, radiation, and nuclear engineering domain. The research has been mainly focused on computer vision tasks applied to medical images. We aim to develop various AI technologies, which would be practically helpful in clinical practice, such as metal artifact reduction or multi-organ segmentation in computed tomography (CT). Currently, we are conducting collaborative research with Seoul National University, Department of Radiology in Seoul National University Hospital, and Department of Radiation Oncology in Samsung Medical Center.
Major research field
Physics-informed Artificial Intelligence (AI), Computer Vision, Medical Imaging (X-ray, CT), Radiation Physics
Desired field of research
Development of various Artificial Intelligence (AI) applications based on domain knowledge of medical, radiation, and nuclear engineering fields
Research Keywords and Topics
• 도메인 지식을 기반으로 한 인공지능 적용 기술 개발
Physics-informed Artificial Intelligence
• 의료영상 기반 분류 및 주요 부위 분할 기술 개발
Classification and Segmentation Technologies for Medical Images
• 의료영상 변환 및 생성 기술 개발
Image-to-Image Translation and Generation Technologies for Medical Images
Research Publications
• IEEE Transactions on Nuclear Science / Compton background elimination for in vivo X-ray fluorescence imaging of gold nanoparticles using convolutional neural network / Seongmoon Jung, Jimin Lee, Hyungjoo Cho, Taeyun Kim, Sung-Joon Ye (cofirst) / 2020-09
• IEEE Access / Deep-learning-based label-free segmentation of cell nuclei in time- lapse refractive index tomograms / Jimin Lee, Hyejin Kim, Hyungjoo Cho, YoungJu Jo, Yujin Song, Daewoong Ahn, Kangwon Lee, YongKeun Park, Sung-Joon Ye / 2019-06
• Physics in Medicine & Biology / Fano cavity test for electron Monte Carlo transport algorithms in magnetic fields: comparison between EGSnrc, PENELOPE, MCNP6 and Geant4 / Jaegi Lee, Jimin Lee, Dongmin Ryu, Hochan Lee, Sung-Joon Ye / 2018-10
Patents
• Heejung Kim, Jimin Lee, Hyungjoo Cho, Sung-Joon Ye, “SYSTEM AND METHOD FOR SEGMENTING NORMAL ORGAN AND/OR TUMOR STRUCTURE BASED ON ARTIFICIAL INTELLIGENCE FOR RADIATION TREATMENT PLANNING,” US 16/946,480 (2020)
• Jimin Lee, Hyungjoo Cho, Hee-Dong Chae, Sung-Joon Ye, “Apparatus and Method for Removing Metal Artifact of Computer Tomography Image Based on Artificial Intelligence,” KR 10-2019-0159149 (2019)