| Deep learning-based image conversion improves the reproducibility of computed tomography radiomics features: a phantom study SB Lee, YJ Cho, Y Hong, D Jeong, J Lee, SH Kim, S Lee, YH Choi Investigative Radiology 57 (5), 308-317, 2022 | 25 | 2022 |
| ComDia+: An interactive visual analytics system for comparing, diagnosing, and improving multiclass classifiers C Park, J Lee, H Han, K Lee 2019 IEEE Pacific Visualization Symposium (PacificVis), 313-317, 2019 | 16 | 2019 |
| Generative adversarial network with radiomic feature reproducibility analysis for computed tomography denoising J Lee, J Jeon, Y Hong, D Jeong, Y Jang, B Jeon, HJ Baek, E Cho, H Shim, ... Computers in Biology and Medicine 159, 106931, 2023 | 8 | 2023 |
| Deep learning-based computed tomography image standardization to improve generalizability of deep learning-based hepatic segmentation SB Lee, Y Hong, YJ Cho, D Jeong, J Lee, SH Yoon, S Lee, YH Choi, ... Korean Journal of Radiology 24 (4), 294, 2023 | 4 | 2023 |
| Improving the Reproducibility of Computed Tomography Radiomic Features Using an Enhanced Hierarchical Feature Synthesis Network D Jeong, Y Hong, J Lee, SB Lee, YJ Cho, H Shim, HJ Chang IEEE Access 12, 27648-27660, 2024 | 2 | 2024 |
| Risk factors based vessel‐specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry HB Park, J Lee, Y Hong, S Byungchang, W Kim, BK Lee, FY Lin, ... Clinical cardiology 46 (3), 320-327, 2023 | 2 | 2023 |
| Self supervised convolutional kernel based handcrafted feature harmonization: Enhanced left ventricle hypertension disease phenotyping on echocardiography J Lee, Y Hong, D Jeong, Y Jang, S Jeong, T Jung, YE Yoon, I Moon, ... arXiv preprint arXiv:2310.08897, 2023 | 1 | 2023 |
| Enhanced hierarchical feature synthesis network for the improvement of computed tomography radiomic features reproducibility D Jeong, Y Hong, J Lee, SB Lee, YJ Cho Available at SSRN 4088395, 2022 | 1 | 2022 |
| Improvement in Image Quality of Low-Dose CT of Canines with Generative Adversarial Network of Anti-Aliasing Generator and Multi-Scale Discriminator Y Son, S Jeong, Y Hong, J Lee, B Jeon, H Choi, J Kim, H Shim Bioengineering 11 (9), 944, 2024 | | 2024 |
| Fully Convolutional Hybrid Fusion Network with Heterogeneous Representations for Identification of S1 and S2 from Phonocardiogram Y Jang, J Jung, Y Hong, J Lee, H Jeong, H Shim, HJ Chang IEEE Journal of Biomedical and Health Informatics, 2024 | | 2024 |
| Artificial intelligence–enhanced electrocardiography analysis as a promising tool for predicting obstructive coronary artery disease in patients with stable angina J Park, J Kim, SH Kang, J Lee, Y Hong, HJ Chang, Y Cho, YE Yoon European Heart Journal-Digital Health, ztae038, 2024 | | 2024 |
| Identifying Coronary Artery Calcification Using Chest X-ray Radiographs and Machine Learning: The Role of the Radiomics Score H Jeong, HB Park, J Hong, J Lee, S Ha, R Heo, J Jung, Y Hong, ... Journal of Thoracic Imaging 39 (2), 119-126, 2024 | | 2024 |
| CT Radiomic Features 의 재현성 향상을 위한 Super-Resolution GAN 기반의 CT 영상 변환 연구 정다운， 이지나， 홍영택， 조연진， 심학준， 장혁재 대한전자공학회 학술대회, 2345-2349, 2020 | | 2020 |
| Wasserstein 생산적 적대 신경망과 구조적 유사지수를 이용한 저선량 컴퓨터 단층촬영 영상 잡음 제거 기법 이지나， 홍영택， 장영걸， 김주호， 백혜진， 하지영， 심학준， 장혁재 한국정보과학회 학술발표논문집, 1851-1853, 2019 | | 2019 |
