Volume-Rendering of Mitochondrial Transports Using VTK. - Yeonggul Jang; Hackjoon Shim; Yoojin Chung (FGIT-ASEA/DRBC/EL, 2011)

Mask-Rendering of Mitochondrial Transports Using VTK. - Yeonggul Jang; Hackjoon Shim; Yoojin Chung (FGIT-DTA/BSBT, 2011)

Core-Shell Detection in Images of Polymer Microbeads. - Yeonggul Jang; Byunghwan Jeon; Yoojin Chung (FGIT-MulGraB/BSBT/IUrC, 2012)

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)

Automatic Segmentation of LV and RV in Cardiac MRI. - Yeonggul Jang; Yoonmi Hong; Seongmin Ha; Sekeun Kim; Hyuk-Jae Chang (STACOM@MICCAI, 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)

Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRI. - Yeonggul Jang; Sekeun Kim; Hackjoon Shim; Hyuk-Jae Chang (STACOM@MICCAI, 2018)

Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images. - Sunghee Jung; Soochahn Lee; Byunghwan Jeon; Yeonggul Jang; Hyuk-Jae Chang (SASHIMI@MICCAI, 2018)

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)

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? - Olivier Bernard 001; Alain Lalande; Clément Zotti; Frederic Cervenansky; Xin Yang 009; Pheng-Ann Heng; Irem Cetin; Karim Lekadir; Oscar Camara 001; Miguel Ángel González Ballester; Gerard Sanroma; Sandy Napel; et al. (IEEE Trans. Medical Imaging, 2018)

A Cascaded Two-step Approach For Segmentation of Thoracic Organs. - Sekeun Kim; Yeonggul Jang; Kyunghoon Han; Hackjoon Shim; Hyuk-Jae Chang (SegTHOR@ISBI, 2019)

Identification of coronary arteries in CT images by Bayesian analysis of geometric relations among anatomical landmarks. - Byunghwan Jeon; Yeonggul Jang; Hackjoon Shim; Hyuk-Jae Chang (Pattern Recognit., 2019)

Deep Learning Cross-Phase Style Transfer for Motion Artifact Correction in Coronary Computed Tomography Angiography. - Sunghee Jung; Soochahn Lee; Byunghwan Jeon; Yeonggul Jang; Hyuk-Jae Chang (IEEE Access, 2020)

Multi-Scale Conditional Generative Adversarial Network for Small-Sized Lung Nodules Using Class Activation Region Influence Maximization. - Kyeongjin Ann; Yeonggul Jang; Hackjoon Shim; Hyuk-Jae Chang (IEEE Access, 2021)

Deep Reinforcement Learning with Explicit Spatio-Sequential Encoding Network for Coronary Ostia Identification in CT Images. - Yeonggul Jang; Byunghwan Jeon (Sensors, 2021)

Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data. - Wufeng Xue; Jiahui Li 005; Zhiqiang Hu; Eric Kerfoot; James R. Clough; Ilkay Öksüz; Hao Xu; Vicente Grau; Fumin Guo; Matthew Ng; Xiang Li 001; Quanzheng Li; et al. (IEEE J. Biomed. Health Informatics, 2021)

Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images. - Kyunghoon Han; Jaeik Jeon; Yeonggul Jang; Sunghee Jung; Sekeun Kim; Hackjoon Shim; Byunghwan Jeon; Hyuk-Jae Chang (Comput. Biol. Medicine, 2022)

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

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)

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction. - Sekeun Kim; Zhenxiang Jiang; Byron A. Zambrano; Yeonggul Jang; Seungik Baek; Sun K. Yoo; Hyuk-Jae Chang (IEEE Trans. Medical Imaging, 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)

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)