| 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 | 249 | 2019 |
| 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, 2019 | 43 | 2019 |
| Deep learning–based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC DW Kim, G Lee, SY Kim, G Ahn, JG Lee, SS Lee, KW Kim, SH Park, ... European Radiology 31, 7047-7057, 2021 | 28 | 2021 |
| Automated segmentation of left ventricular myocardium on cardiac computed tomography using deep learning HJ Koo, JG Lee, JY Ko, G Lee, JW Kang, YH Kim, DH Yang Korean journal of radiology 21 (6), 660, 2020 | 26 | 2020 |
| A curriculum learning strategy to enhance the accuracy of classification of various lesions in chest-PA X-ray screening for pulmonary abnormalities B Park, Y Cho, G Lee, SM Lee, YH Cho, ES Lee, KH Lee, JB Seo, N Kim Scientific reports 9 (1), 15352, 2019 | 25 | 2019 |
| Deep chest X‐ray: detection and classification of lesions based on deep convolutional neural networks Y Cho, SM Lee, YH Cho, JG Lee, B Park, G Lee, N Kim, JB Seo International Journal of Imaging Systems and Technology 31 (1), 72-81, 2021 | 6 | 2021 |
| Automatic hepatocellular carcinoma lesion detection with dynamic enhancement characteristic from multi-phase CT images G Lee, J Kim, JG Lee, G Ahn, SH Park, SY Kim, KW Kim, SS Lee, N Kim International Forum on Medical Imaging in Asia 2019 11050, 203-208, 2019 | 3 | 2019 |
| Automatic Hepatocellular Carcinoma Lesion Detection on Multi-phase CT Images using Transfer Learning and Multi-channel Information G Lee, J Kim, JG Lee, G Ahn, SH Park, SY Kim, KW Kim, SS Lee, N Kim | | 2018 |
