| Deep learning in medical imaging: general overview JG Lee, S Jun, YW Cho, H Lee, GB Kim, JB Seo, N Kim Korean journal of radiology 18 (4), 570-584, 2017 | 1490 | 2017 |
| Deep learning–based image conversion of CT reconstruction kernels improves radiomics reproducibility for pulmonary nodules or masses J Choe, SM Lee, KH Do, G Lee, JG Lee, SM Lee, JB Seo Radiology 292 (2), 365-373, 2019 | 273 | 2019 |
| CycleMorph: cycle consistent unsupervised deformable image registration B Kim, DH Kim, SH Park, J Kim, JG Lee, JC Ye Medical image analysis 71, 102036, 2021 | 255 | 2021 |
| Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net J Yun, J Park, D Yu, J Yi, M Lee, HJ Park, JG Lee, JB Seo, N Kim Medical image analysis 51, 13-20, 2019 | 125 | 2019 |
| Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network H Kim, J Jung, J Kim, B Cho, J Kwak, JY Jang, S Lee, JG Lee, SM Yoon Scientific reports 10 (1), 6204, 2020 | 101 | 2020 |
| Methods for clinical evaluation of artificial intelligence algorithms for medical diagnosis SH Park, K Han, HY Jang, JE Park, JG Lee, DW Kim, J Choi Radiology 306 (1), 20-31, 2023 | 80 | 2023 |
| Angiography‐based machine learning for predicting fractional flow reserve in intermediate coronary artery lesions H Cho, JG Lee, SJ Kang, WJ Kim, SY Choi, J Ko, HS Min, GH Choi, ... Journal of the American Heart Association 8 (4), e011685, 2019 | 79 | 2019 |
| Fully automated segmentation of cartilage from the MR images of knee using a multi‐atlas and local structural analysis method JG Lee, S Gumus, CH Moon, CK Kwoh, KT Bae Medical physics 41 (9), 092303, 2014 | 73 | 2014 |
| Deep learning algorithm for reducing CT slice thickness: effect on reproducibility of radiomic features in lung cancer S Park, SM Lee, KH Do, JG Lee, W Bae, H Park, KH Jung, JB Seo Korean journal of radiology 20 (10), 1431-1440, 2019 | 70 | 2019 |
| Development of an automatic classification system for differentiation of obstructive lung disease using HRCT N Kim, JB Seo, Y Lee, JG Lee, SS Kim, SH Kang Journal of digital imaging 22, 136-148, 2009 | 60 | 2009 |
| Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation H Hae, SJ Kang, WJ Kim, SY Choi, JG Lee, Y Bae, H Cho, DH Yang, ... PLoS Medicine 15 (11), e1002693, 2018 | 56 | 2018 |
| Volume doubling times of lung adenocarcinomas: correlation with predominant histologic subtypes and prognosis S Park, SM Lee, S Kim, JG Lee, S Choi, KH Do, JB Seo Radiology 295 (3), 703-712, 2020 | 52 | 2020 |
| CT image conversion among different reconstruction kernels without a sinogram by using a convolutional neural network SM Lee, JG Lee, G Lee, J Choe, KH Do, N Kim, JB Seo Korean journal of radiology 20 (2), 295-303, 2019 | 52 | 2019 |
| Performance testing of several classifiers for differentiating obstructive lung diseases based on texture analysis at high-resolution computerized tomography (HRCT) Y Lee, JB Seo, JG Lee, SS Kim, N Kim, SH Kang Computer methods and programs in biomedicine 93 (2), 206-215, 2009 | 52 | 2009 |
| Intravascular ultrasound-based machine learning for predicting fractional flow reserve in intermediate coronary artery lesions JG Lee, J Ko, H Hae, SJ Kang, DY Kang, PH Lee, JM Ahn, DW Park, ... Atherosclerosis 292, 171-177, 2020 | 50 | 2020 |
| Prediction of coronary stent underexpansion by pre-procedural intravascular ultrasound–based deep learning HS Min, D Ryu, SJ Kang, JG Lee, JH Yoo, H Cho, DY Kang, PH Lee, ... Cardiovascular Interventions 14 (9), 1021-1029, 2021 | 47 | 2021 |
| Fully automatic coronary calcium score software empowered by artificial intelligence technology: validation study using three CT cohorts JG Lee, HS Kim, H Kang, HJ Koo, JW Kang, YH Kim, DH Yang Korean Journal of Radiology 22 (11), 1764, 2021 | 45 | 2021 |
| Computer-aided detection of colonic polyps at CT colonography using a Hessian matrix–based algorithm: preliminary study SH Kim, JM Lee, JG Lee, JH Kim, PA Lefere, JK Han, BI Choi American Journal of Roentgenology 189 (1), 41-51, 2007 | 45 | 2007 |
| Automated detection of vulnerable plaque in intravascular ultrasound images TJ Jun, SJ Kang, JG Lee, J Kweon, W Na, D Kang, D Kim, D Kim, YH Kim Medical & biological engineering & computing 57, 863-876, 2019 | 44 | 2019 |
| Informatics in radiology: dual-energy electronic cleansing for fecal-tagging CT colonography W Cai, SH Kim, JG Lee, H Yoshida Radiographics 33 (3), 891-912, 2013 | 44 | 2013 |
