Yohan Jun

发表

Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors

Sung Soo Ahn, D. Hwang, Ho-Joon Lee, 2018, Scientific Reports.

어텐션 기법 및 의료 영상에의 적용에 관한 최신 동향

D. Hwang, Jeongryong Lee, Yohan Jun, 2020, Taehan Yongsang Uihakhoe chi.

Megahertz-wave-transmitting conducting polymer electrode for device-to-device integration

Shinill Kang, J. Cheon, D. Hwang, 2019, Nature Communications.

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction pdf

Jean-Luc Starck, Philippe Ciuciu, Dosik Hwang, 2021, IEEE Transactions on Medical Imaging.

Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge

Daniel Rueckert, Mariya Doneva, Vishal M. Patel, 2021, MLMIR@MICCAI.

Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces

Hong-Goo Kang, D. Hwang, Huanyu Cheng, 2022, Nature Communications.

State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge

Jean-Luc Starck, Anuroop Sriram, Y. Lui, 2020, ArXiv.

Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging

D. Hwang, Kyunghwa Han, Yohan Jun, 2021, European Radiology.

SSL‐QALAS: Self‐Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D‐QALAS

B. Gagoski, B. Bilgiç, Xiaoqing Wang, 2023, Magnetic resonance in medicine.

Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors

Sung Soo Ahn, D. Hwang, Ho-Joon Lee, 2018, Scientific Reports.

Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning

Sung Soo Ahn, D. Hwang, Kyunghwa Han, 2023, European Radiology.

Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method

Taejoon Eo, Dosik Hwang, Yohan Jun, 2021, Medical Image Anal..

KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images

Taeseong Kim, Jinseong Jang, Taejoon Eo, 2018, Magnetic resonance in medicine.

COSMOS: Cross-Modality Unsupervised Domain Adaptation for 3D Medical Image Segmentation based on Target-aware Domain Translation and Iterative Self-Training

Yohan Jun, Taejoon Eo, Hyungseob Shin, 2022, ArXiv.

Accelerating Cartesian MRI by domain-transform manifold learning in phase-encoding direction

Taejoon Eo, Dosik Hwang, Yohan Jun, 2020, Medical Image Anal..

High‐SNR multiple T2(*)‐contrast magnetic resonance imaging using a robust denoising method based on tissue characteristics

Taeseong Kim, Hongpyo Lee, Taejoon Eo, 2017, Journal of magnetic resonance imaging : JMRI.

Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI

Da Hyun Lee, H. Kim, Yohan Jun, 2023, European Radiology.

Zero‐DeepSub: Zero‐shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D‐QALAS

B. Gagoski, B. Bilgiç, C. Jaimes, 2023, Magnetic resonance in medicine.

Joint Deep Model-based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet) for Fast MRI

Taejoon Eo, Dosik Hwang, Yohan Jun, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Parallel imaging in time‐of‐flight magnetic resonance angiography using deep multistream convolutional neural networks

Taeseong Kim, Taejoon Eo, Dosik Hwang, 2019, Magnetic resonance in medicine.

Improved Multi-Shot Diffusion-Weighted MRI with Zero-Shot Self-Supervised Learning Reconstruction

B. Bilgiç, Xiaoqing Wang, Yohan Jun, 2023, 2308.05103.

Megahertz-wave-transmitting conducting polymer electrode for device-to-device integration

Shinill Kang, J. Cheon, D. Hwang, 2019, Nature Communications.

SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation

Yohan Jun, Taejoon Eo, Hyungseob Shin, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Self-Training Based Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation pdf

Taejoon Eo, Dosik Hwang, Yohan Jun, 2021, ArXiv.