QuIIL focuses on computational methods to process and analyze imaging/non-imaging data. The primary interest of our group is to develop, standardize, and validate advanced computational methods for extracting quantifiable patterns/features, discovering useful/meaninfgul knowledge, and resolving real-world problems.
Our research activities include medical imaging, image processing, pattern recognition, artificial intelligence, machine learning, deep learning, and data mining. Our approaches have been applied to medical images (pathology and radiology images) and agricultural images.
We collaborate with a number of investigators in and outside of Korea: Asan Medical Center, Konkuk University Medical Center, Daejeon St. Mary's Hospital, Kangbuk Samsung Medical Center (Korea), National Institutes of Health, University of Illinois at Urbana-Champaign, University of Illinois at Chicago (USA), Warwick University (UK), University of British Columbia, Queen's University (Canada).