Yeonggul Jang

发表

Assessment of Image Quality for Selective Intracoronary Contrast-Injected CT Angiography in a Hybrid Angio-CT System: A Feasibility Study in Swine

Hyuk-Jae Chang, H. Shim, Byoung‐Kwon Lee, 2021, Yonsei medical journal.

Clinical feasibility of catheter-directed selective intracoronary computed tomography angiography using an extremely low dose of iodine in patients with coronary artery disease

Hyuk-Jae Chang, H. Shim, Y. Jang, 2018, European Radiology.

Feasibility of Selective Catheter-Directed Coronary Computed Tomography Angiography Using Ultralow-Dose Intracoronary Contrast Injection in a Swine Model

Hyuk-Jae Chang, H. Shim, Byoung‐Kwon Lee, 2015, Investigative radiology.

Diagnostic Accuracy of a Novel On-site Virtual Fractional Flow Reserve Parallel Computing System

Hyuk-Jae Chang, Sekeun Kim, S. Ha, 2020, Yonsei medical journal.

Multi-Scale Conditional Generative Adversarial Network for Small-Sized Lung Nodules Using Class Activation Region Influence Maximization

Hyuk-Jae Chang, H. Shim, Yeonggul Jang, 2021, IEEE Access.

Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification

H. Shim, Sekeun Kim, Youngtaek Hong, 2022, ArXiv.

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

Xin Yang, Pheng-Ann Heng, Peter M. Full, 2018, IEEE Transactions on Medical Imaging.

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction

Hyuk-Jae Chang, Sekeun Kim, S. Baek, 2022, IEEE Transactions on Medical Imaging.

Automatic aortic valve landmark localization in coronary CT angiography using colonial walk

Walid Abdullah Al, Ho Yub Jung, Il Dong Yun, 2018, PloS one.

A Cascaded Two-step Approach For Segmentation of Thoracic Organs

Yeonggul Jang, Hackjoon Shim, Hyuk-Jae Chang, 2019, SegTHOR@ISBI.

Maximum a posteriori estimation method for aorta localization and coronary seed identification

Yeonggul Jang, Dongjin Han, Seongmin Ha, 2017, Pattern Recognit..

Deep Reinforcement Learning with Explicit Spatio-Sequential Encoding Network for Coronary Ostia Identification in CT Images

Byunghwan Jeon, Yeonggul Jang, Yeonggul Jang, 2021, Sensors.

Viability assessment after conventional coronary angiography using a novel cardiovascular interventional therapeutic CT system: Comparison with gross morphology in a subacute infarct swine model.

Hyuk-Jae Chang, J. Min, H. Shim, 2015, Journal of cardiovascular computed tomography.

Quantitative Assessment of Foot Blood Flow by Using Dynamic Volume Perfusion CT Technique: A Feasibility Study.

Dong Yeon Lee, S. Min, S. Min, 2016, Radiology.

Identification of coronary arteries in CT images by Bayesian analysis of geometric relations among anatomical landmarks

Yeonggul Jang, Hackjoon Shim, Hyuk-Jae Chang, 2019, Pattern Recognit..

Benchmarking Deep Learning Frameworks for Automated Diagnosis of Ocular Toxoplasmosis: A Comprehensive Approach to Classification and Segmentation

Shams Nafisa Ali, Samiul Based Shuvo, Yeonggul Jang, 2023, ArXiv.

Automatic Coronary Artery Segmentation Using Active Search for Branches and Seemingly Disconnected Vessel Segments from Coronary CT Angiography

Yeonggul Jang, Hyuk-Jae Chang, Seongmin Ha, 2016, PloS one.

Generation of Triangular Mesh of Coronary Artery Using Mesh Merging

H. Shim, Yeonggul Jang, Byunghwan Jeon, 2016 .

Generative adversarial network with radiomic feature reproducibility analysis for computed tomography denoising

H. Shim, H. Baek, Youngtaek Hong, 2023, Comput. Biol. Medicine.

Automatic Segmentation of LV and RV in Cardiac MRI

Yeonggul Jang, Seongmin Ha, Yoonmi Hong, 2017, STACOM@MICCAI.

Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data

Georgios Tziritas, Eric Kerfoot, Jin Ma, 2021, IEEE Journal of Biomedical and Health Informatics.

Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound Images

Yeonggul Jang, Youngtaek Hong, Hackjoon Shim, 2018, CVII-STENT/LABELS@MICCAI.

Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRI

Yeonggul Jang, Hackjoon Shim, Hyuk-Jae Chang, 2018, STACOM@MICCAI.

Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images

H. Shim, Sekeun Kim, Sunghee Jung, 2021, Comput. Biol. Medicine.

Artificial intelligence-enhanced automation for M-mode echocardiographic analysis: ensuring fully automated, reliable, and reproducible measurements.

Y. Yoon, S. Ha, Sunghee Jung, 2024, The international journal of cardiovascular imaging.

Improving Out-of-Distribution Detection in Echocardiographic View Classication through Enhancing Semantic Features

Y. Yoon, S. Ha, Youngtaek Hong, 2023, 2308.16483.