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Youngtaek Hong
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2020 – today
- 2024
- [j6]Dawun Jeong
, Youngtaek Hong
Improving the Reproducibility of Computed Tomography Radiomic Features Using an Enhanced Hierarchical Feature Synthesis Network. IEEE Access 12: 27648-27660 (2024) - [c6]Jaeik Jeon, Jiyeon Kim, Yeonggul Jang, Yeonyee E. Yoon, Dawun Jeong, Youngtaek Hong, Seung-Ah Lee, Hyuk-Jae Chang:
A Unified Approach For Comprehensive Analysis of Various Spectral and Tissue Doppler Echocardiography. ISBI 2024: 1-5 - 2023
- [j5]Kyunghoon Han
Reconstruction of Partially Broken Vascular Structures in X-Ray Images via Vesselness-Loss-Based Multi-Scale Generative Adversarial Networks. IEEE Access 11: 86335-86350 (2023) - [j4]Jina Lee
Generative adversarial network with radiomic feature reproducibility analysis for computed tomography denoising. Comput. Biol. Medicine 159: 106931 (2023) - [i4]Jaeik Jeon, Seongmin Ha, Yeonyee E. Yoon, Jiyeon Kim, Hyunseok Jeong, Dawun Jeong, Yeonggul Jang, Youngtaek Hong, Hyuk-Jae Chang:
Echocardiographic View Classification with Integrated Out-of-Distribution Detection for Enhanced Automatic Echocardiographic Analysis. CoRR abs/2308.16483 (2023) - [i3]Jina Lee, Youngtaek Hong, Dawun Jeong, Yeonggul Jang, Sihyeon Jeong, Taekgeun Jung, Yeonyee E. Yoon, Inki Moon, Seung-Ah Lee, Hyuk-Jae Chang:
Self supervised convolutional kernel based handcrafted feature harmonization: Enhanced left ventricle hypertension disease phenotyping on echocardiography. CoRR abs/2310.08897 (2023) - [i2]Jaeik Jeon, Jiyeon Kim, Yeonggul Jang, Yeonyee E. Yoon, Dawun Jeong, Youngtaek Hong, Seung-Ah Lee, Hyuk-Jae Chang:
A Unified Approach for Comprehensive Analysis of Various Spectral and Tissue Doppler Echocardiography. CoRR abs/2311.08439 (2023) - 2022
- [i1]Jaeik Jeon, Yeonggul Jang, Youngtaek Hong, Hackjoon Shim, Sekeun Kim:
Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification. CoRR abs/2207.01868 (2022)
2010 – 2019
- 2019
- [c5]Youngtaek Hong, Yeosun Kyung, Seong-Lyun Kim:
A Multi-Robot Cooperative Patrolling Algorithm with Sharing Multiple Cycles. EuCNC 2019: 300-304 - [c4]Youngtaek Hong, Frederic Commandeur, Sebastien Cadet, Markus Goeller, Mhairi Doris, Xi Chen
Deep learning-based stenosis quantification from coronary CT angiography. Image Processing 2019: 109492I - 2018
- [c3]Sekeun Kim, Yeonggul Jang, Byunghwan Jeon, Youngtaek Hong, Hackjoon Shim, Hyuk-Jae Chang:
Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound Images. CVII-STENT/LABELS@MICCAI 2018: 161-168 - 2017
- [j3]Byunghwan Jeon, Yoonmi Hong, Dongjin Han, Yeonggul Jang, Sunghee Jung
Maximum a posteriori estimation method for aorta localization and coronary seed identification. Pattern Recognit. 68: 222-232 (2017) - [c2]Youngtaek Hong, Yoonmi Hong
Coronary luminal and wall mask prediction using convolutional neural network. ISBI 2017: 1049-1052 - [c1]Taewoo Park, Seung Yeon Shin, Youngtaek Hong, Soochahn Lee, Hyuk-Jae Chang, Il Dong Yun:
Nonrigid 2D registration of fluoroscopic coronary artery image sequence with propagated deformation field. Biomedical Applications in Molecular, Structural, and Functional Imaging 2017: 101371W - 2016
- [j2]Yeonggul Jang, Ho Yub Jung, Youngtaek Hong, Iksung Cho
Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images. Comput. Math. Methods Medicine 2016: 4561979:1-4561979:7 (2016) - 2014
- [j1]Dongjin Han, Nam-Thai Doan, Hackjoon Shim, Byunghwan Jeon, Hyunna Lee, Youngtaek Hong, Hyuk-Jae Chang
A fast seed detection using local geometrical feature for automatic tracking of coronary arteries in CTA. Comput. Methods Programs Biomed. 117(2): 179-188 (2014)
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