A fast seed detection using local geometrical feature for automatic tracking of coronary arteries in CTA. - Dongjin Han; Nam-Thai Doan; Hackjoon Shim; Byunghwan Jeon; Hyunna Lee; Youngtaek Hong; Hyuk-Jae Chang (Comput. Methods Programs Biomed., 2014)

Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images. - Yeonggul Jang; Ho Yub Jung; Youngtaek Hong; Iksung Cho; Hackjoon Shim; Hyuk-Jae Chang (Comput. Math. Methods Medicine, 2016)

Coronary luminal and wall mask prediction using convolutional neural network. - Youngtaek Hong; Yoonmi Hong; Yeonggul Jang; Sekeun Kim; Byunghwan Jeon; Sunghee Jung; Seongmin Ha; Dongjin Han; Hackjoon Shim; Hyuk-Jae Chang (ISBI, 2017)

Nonrigid 2D registration of fluoroscopic coronary artery image sequence with propagated deformation field. - Taewoo Park; Seung Yeon Shin; Youngtaek Hong; Soochahn Lee; Hyuk-Jae Chang; Il Dong Yun (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2017)

Maximum a posteriori estimation method for aorta localization and coronary seed identification. - Byunghwan Jeon; Yoonmi Hong; Dongjin Han; Yeonggul Jang; Sunghee Jung; Youngtaek Hong; Seongmin Ha; Hackjoon Shim; Hyuk-Jae Chang (Pattern Recognit., 2017)

Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound Images. - Sekeun Kim; Yeonggul Jang; Byunghwan Jeon; Youngtaek Hong; Hackjoon Shim; Hyuk-Jae Chang (CVII-STENT/LABELS@MICCAI, 2018)

A Multi-Robot Cooperative Patrolling Algorithm with Sharing Multiple Cycles. - Youngtaek Hong; Yeosun Kyung; Seong-Lyun Kim (EuCNC, 2019)

Deep learning-based stenosis quantification from coronary CT angiography. - Youngtaek Hong; Frederic Commandeur; Sebastien Cadet; Markus Goeller; Mhairi Doris; Xi Chen 053; Jacek Kwiecinski; Daniel S. Berman; Piotr J. Slomka; Hyuk-Jae Chang; Damini Dey (Image Processing, 2019)

Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification. - Jaeik Jeon; Yeonggul Jang; Youngtaek Hong; Hackjoon Shim; Sekeun Kim (CoRR, 2022)

Reconstruction of Partially Broken Vascular Structures in X-Ray Images via Vesselness-Loss-Based Multi-Scale Generative Adversarial Networks. - Kyunghoon Han; Heejoon Koo; Sunghee Jung; Hyung-Bok Park; Youngtaek Hong; Hackjoon Shim; Byunghwan Jeon; Hyuk-Jae Chang (IEEE Access, 2023)

Echocardiographic View Classification with Integrated Out-of-Distribution Detection for Enhanced Automatic Echocardiographic Analysis. - Jaeik Jeon; Seongmin Ha; Yeonyee E. Yoon; Jiyeon Kim; Hyunseok Jeong; Dawun Jeong; Yeonggul Jang; Youngtaek Hong; Hyuk-Jae Chang (CoRR, 2023)

Self supervised convolutional kernel based handcrafted feature harmonization: Enhanced left ventricle hypertension disease phenotyping on echocardiography. - Jina Lee; Youngtaek Hong; Dawun Jeong; Yeonggul Jang; Sihyeon Jeong; Taekgeun Jung; Yeonyee E. Yoon; Inki Moon; Seung-Ah Lee; Hyuk-Jae Chang (CoRR, 2023)

Generative adversarial network with radiomic feature reproducibility analysis for computed tomography denoising. - Jina Lee; Jaeik Jeon; Youngtaek Hong; Dawun Jeong; Yeonggul Jang; Byunghwan Jeon; Hye Jin Baek; Eun Cho; Hackjoon Shim; Hyuk-Jae Chang (Comput. Biol. Medicine, 2023)

A Unified Approach For Comprehensive Analysis of Various Spectral and Tissue Doppler Echocardiography. - Jaeik Jeon; Jiyeon Kim; Yeonggul Jang; Yeonyee E. Yoon; Dawun Jeong; Youngtaek Hong; Seung-Ah Lee; Hyuk-Jae Chang (ISBI, 2024)

Improving the Reproducibility of Computed Tomography Radiomic Features Using an Enhanced Hierarchical Feature Synthesis Network. - Dawun Jeong; Youngtaek Hong; Jina Lee; Seul Bi Lee; Yeon Jin Cho; Hackjoon Shim; Hyuk-Jae Chang (IEEE Access, 2024)

Fully Convolutional Hybrid Fusion Network With Heterogeneous Representations for Identification of S1 and S2 From Phonocardiogram. - Yeonggul Jang; Juyeong Jung; Youngtaek Hong; Jina Lee; Hyunseok Jeong; Hackjoon Shim; Hyuk-Jae Chang (IEEE J. Biomed. Health Informatics, 2024)