Juhwan Lee will develop new AI methods for CCTA evaluations of high-risk coronary atherosclerotic plaque by comparing to concurrently-acquired, high resolution/contrast IVOCT images, deemed the best method to access high-risk plaque. Technical innovations will include highly automated assessment of IVOCT and CCTA features, accurate IVOCT to CCTA registration, and novel, well-matched AI analyses.
- J. Lee, et al., Segmentation of coronary calcified plaque in intravascular OCT images using a two-step deep learning approach, IEEE Access, 8, 225581, 2020.
- J. Lee, et al., Fully automated plaque characterization in intravascular OCT images using hybrid convolutional and lumen morphology features, Nature - Scientific Reports, 10(1), 2596, 2020.
- H. Lu, J. Lee, et al., Application and evaluation of highly automated software for comprehensive stent analysis in intravascular optical coherence tomography, Nature - Scientific Reports, 10, 2150, 2020.