J. C. Ye

J. C. Ye, Youngchan Kim, D. Yee, 2009, 2009 Conference on Lasers and Electro-Optics and 2009 Conference on Quantum electronics and Laser Science Conference.

Cramer-Rao bounds for 2-D target shape estimation in nonlinear inverse scattering problems with application to passive radar

Pierre Moulin, Yoram Bresler, J. C. Ye, 2001 .

Enhancement of terahertz pulse emission by optical nanoantenna.

Jong Chul Ye, Kyong Hwan Jin, Jaewook Ahn, 2012, ACS nano.

Cramer-Rao bounds for parametric shape estimation in inverse problems

J. C. Ye, Y. Bresler, P. Moulin, 2002, IEEE Trans. Image Process..

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

Nicolas Olivier, Suliana Manley, Jong Chul Ye, 2014, Scientific Reports.

Low-rank Fourier interpolation for compressed sensing imaging

J. C. Ye, 2016 .

Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems pdf

Jong Chul Ye, Gyutaek Oh, Byeongsu Sim, 2019, ArXiv.

Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal

Jong Chul Ye, Kyong Hwan Jin, J. C. Ye, 2018, IEEE Transactions on Image Processing.

Cramér-Rao Bounds for Parametric Estimation of Target Boundaries in Nonlinear Inverse Scattering Problems

J. C. Ye, Y. Bresler, 2007 .

Multiscale Interior Tomography Using 1D Generalized Total Variation

Michael Unser, Jong Chul Ye, John Paul Ward, 2014 .

Fluorescent microscopy beyond diffraction limits using speckle illumination and joint support recovery

Jong Chul Ye, Jaeduck Jang, Chulhee Choi, 2013, Scientific Reports.

Whole‐brain perfusion imaging with balanced steady‐state free precession arterial spin labeling

Jong Chul Ye, Eung Yeop Kim, Sung-Hong Park, 2016, NMR in biomedicine.

Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data pdf

Jong Chul Ye, Hyungjin Chung, Leonard Sunwoo, 2020, Medical Image Anal..

Continuous Conversion of CT Kernel Using Switchable CycleGAN With AdaIN pdf

Jong Chul Ye, Eung Yeop Kim, Serin Yang, 2020, IEEE Transactions on Medical Imaging.

Unsupervised resolution-agnostic quantitative susceptibility mapping using adaptive instance normalization

J. C. Ye, Sung-Hong Park, Gyutaek Oh, 2022, Medical Image Anal..

Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm

Dong Yul Oh, J. C. Ye, Ji Hoon Park, 2020, Korean journal of radiology.

Improving Diffusion Models for Inverse Problems using Manifold Constraints

J. C. Ye, Byeongsu Sim, Hyungjin Chung, 2022, Neural Information Processing Systems.

Development of digital breast tomosynthesis and diffuse optical tomography fusion imaging for breast cancer detection

J. C. Ye, D. Heo, H. Kim, 2020, Scientific Reports.

TOPOLOGICAL DATA RECOVERY UNDER COMPRESSED SENSING

J. C. Ye, P. Kim, M. Chung, 2010 .

Multiple Measurement Vector Problem with Subspace-based Algorithm

Jong Chul Ye, J. C. Ye, Jm Kim, 2010 .

Telecentric f-theta Lens for high-speed terahertz reflection three-dimensional imaging

J. C. Ye, D. Yee, K. Jin, 2014, 2014 39th International Conference on Infrared, Millimeter, and Terahertz waves (IRMMW-THz).

True Temporal Resolution TWIST Imaging using Annihilating Filter-based Low-rank wrap around Hankel Matrix

Jong Chul Ye, Kyong Hwan Jin, Eung Yeop Kim, 2017 .

Compressed Sensing of FRI Signals using Annihilating Filter-based Low-rank Interpolation

J. C. Ye, 2016 .

Modified k-t BLAST without training data set using FOCUSS

Jong Chul Ye, J. C. Ye, H Jung, 2006 .

A Self-Referencing Level-Set Method for Image Reconstruction from Sparse Fourier Samples

J. C. Ye, Y. Bresler, P. Moulin, 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

Diffusion Posterior Sampling for General Noisy Inverse Problems

Michael T. McCann, J. C. Ye, M. Klasky, 2022, ArXiv.

Contrast Agent Removal for Brain CT Angiography Using Switchable CycleGAN with AdaIN and Histogram Equalization

J. C. Ye, Boah Kim, Eung Yeop Kim, 2022, 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS).

Subwavelength silicon honeycomb structure for tailored index in terahertz broadband region

J. C. Ye, K. Jeong, K. Jin, 2012, 2012 International Conference on Optical MEMS and Nanophotonics.

Use of Salvage Surgery or Stereotactic Radiosurgery for Multiply Recurrent Skull Base Chordomas: A Single-Institution Experience and Review of the Literature

J. C. Ye, Cheng Yu, M. Weiss, 2020, Journal of Neurological Surgery Part B: Skull Base.

Parallel Diffusion Models of Operator and Image for Blind Inverse Problems

J. C. Ye, Sehui Kim, Hyungjin Chung, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Diffusion Posterior Sampling for General Noisy Inverse Problems

Michael T. McCann, J. C. Ye, M. Klasky, 2022, ArXiv.

Solving 3D Inverse Problems Using Pre-Trained 2D Diffusion Models

Michael T. McCann, J. C. Ye, M. Klasky, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Generative Models for Inverse Imaging Problems: From mathematical foundations to physics-driven applications

J. C. Ye, Y. Bresler, Zhizhen Zhao, 2023, IEEE Signal Processing Magazine.

Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis

Jong Chul Ye, J. C. Ye, Byung-Hoon Kim, 2020, Frontiers in Neuroscience.

Nonlinear multigrid algorithms for Bayesian optical diffusion tomography

Charles A. Bouman, Jong Chul Ye, Rick P. Millane, 2001, IEEE Trans. Image Process..

Optical diffusion tomography by iterative- coordinate-descent optimization in a Bayesian framework

Charles A. Bouman, Jong Chul Ye, Rick P. Millane, 1999 .

Interior Tomography Using 1D Generalized Total Variation. Part II: Multiscale Implementation

Michael Unser, Jong Chul Ye, Yoseob Han, 2015, SIAM J. Imaging Sci..

Interior Tomography Using 1D Generalized Total Variation. Part I: Mathematical Foundation

Michael Unser, Jong Chul Ye, John Paul Ward, 2015, SIAM J. Imaging Sci..

Improved k–t BLAST and k–t SENSE using FOCUSS

Jong Chul Ye, Hong Jung, Eung Yeop Kim, 2007, Physics in medicine and biology.

Deep residual learning for compressed sensing MRI

Jong Chul Ye, Dongwook Lee, Jae Jun Yoo, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Random impulse noise removal using sparse and low rank decomposition of annihilating filter-based Hankel matrix

Jong Chul Ye, Kyong Hwan Jin, J. C. Ye, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Sparse + Low Rank Decomposition of Annihilating Filter-based Hankel Matrix for Impulse Noise Removal pdf

Jong Chul Ye, Kyong Hwan Jin, J. C. Ye, 2015, ArXiv.

Statistical analysis of fNIRS data: A comprehensive review

Sungho Tak, Jong Chul Ye, J. C. Ye, 2014, NeuroImage.

A Unified Sparse Recovery and Inference Framework for Functional Diffuse Optical Tomography Using Random Effect Model

Sungho Tak, Jong Chul Ye, Ok Kyun Lee, 2015, IEEE Transactions on Medical Imaging.

Compressed sensing reconstruction of statistical parameter map for functional diffuse optical tomography

Hua Li, Sungho Tak, Jong Chul Ye, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

Source Localization Approach for Functional Dot Using Music and Fdr Control References and Links

Jong Chul Ye, Ok Kyun Lee, J. C. Ye, 2022 .

Severity Quantification and Lesion Localization of COVID-19 on CXR using Vision Transformer

J. C. Ye, Sang Min Lee, J. Seo, 2021, ArXiv.

Understanding Geometry of Encoder-Decoder CNNs

Jong Chul Ye, J. C. Ye, Woon Kyoung Sung, 2019, ICML.

Topological persistence vineyard for dynamic functional brain connectivity during resting and gaming stages

Jaejun Yoo, Jong Chul Ye, Eun Young Kim, 2016, Journal of Neuroscience Methods.

Asymptotic global confidence regions in parametric shape estimation problems

Pierre Moulin, Jong Chul Ye, Yoram Bresler, 2000, IEEE Trans. Inf. Theory.

CollaGAN: Collaborative GAN for Missing Image Data Imputation

Jong Chul Ye, Dongwook Lee, Won-Jin Moon, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets

Jong Chul Ye, Sangjoon Park, J. C. Ye, 2020, IEEE Transactions on Medical Imaging.

NIRS-SPM: Statistical parametric mapping for near-infrared spectroscopy

Sungho Tak, Jong Chul Ye, Kwang Eun Jang, 2009, NeuroImage.

Comparative study of iterative reconstruction algorithms for missing cone problems in optical diffraction tomography.

Jong Chul Ye, Kyong Hwan Jin, YongKeun Park, 2015, Optics express.

Breast cancer diagnosis from fluorescence spectroscopy using support vector machine

Doheon Lee, Jong Chul Ye, Jiyoung Choi, 2007, SPIE BiOS.

Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning

Jeffrey A. Fessler, Jong Chul Ye, Saiprasad Ravishankar, 2019, Proceedings of the IEEE.

Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT

Jong Chul Ye, Yoseob Han, J. C. Ye, 2017, IEEE Transactions on Medical Imaging.

Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network

Jaejun Yoo, Jong Chul Ye, Eunhee Kang, 2018, IEEE Transactions on Medical Imaging.

Diagnosis of coronary layered plaque by deep learning

J. C. Ye, I. Jang, A. Nakajima, 2022, Scientific Reports.

Artificial Intelligence in Health Care: Current Applications and Issues

Seungwook Paek, Jong Chul Ye, Namkug Kim, 2020, Journal of Korean medical science.

Variational Formulation of Unsupervised Deep Learning for Ultrasound Image Artifact Removal

J. C. Ye, Shujaat Khan, Jaeyoung Huh, 2021, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

Unsupervised Denoising for Satellite Imagery Using Wavelet Directional CycleGAN

Jong Chul Ye, Joonyoung Song, Doochun Seo, 2021, IEEE Transactions on Geoscience and Remote Sensing.

Unsupervised Denoising for Satellite Imagery using Wavelet Subband CycleGAN pdf

Jong Chul Ye, Joonyoung Song, Doo-Chun Seo, 2020, ArXiv.

Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification

Jong Chul Ye, Woong Bae, Jae Jun Yoo, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Deep learning for tomographic image reconstruction

Jong Chul Ye, Bruno De Man, Ge Wang, 2020, Nature Machine Intelligence.

Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis pdf

Jong Chul Ye, Yoseob Han, Jae Jun Yoo, 2016, ArXiv.

Unsupervised CT Metal Artifact Learning using Attention-guided beta-CycleGAN pdf

Jong Chul Ye, Junghyun Lee, Jawook Gu, 2020, ArXiv.

Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal pdf

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2020, ArXiv.

Assessing the importance of magnetic resonance contrasts using collaborative generative adversarial networks

Jong Chul Ye, Won-Jin Moon, J. C. Ye, 2020, Nature Machine Intelligence.

Deep learning with domain adaptation for accelerated projection‐reconstruction MR

Jong Chul Ye, Yoseob Han, Jae Jun Yoo, 2018, Magnetic resonance in medicine.

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Jong Chul Ye, Jong Min Kim, Kyong Hwan Jin, 2015, IEEE Transactions on Information Theory.

Deep artifact learning for compressed sensing and parallel MRI pdf

Jong Chul Ye, Dongwook Lee, Jae Jun Yoo, 2017, ArXiv.

Radial k‐t FOCUSS for high‐resolution cardiac cine MRI

Jong Chul Ye, Hong Jung, Jaeseok Park, 2010, Magnetic resonance in medicine.

Cycle‐consistent adversarial denoising network for multiphase coronary CT angiography

Jong Chul Ye, Eunhee Kang, Dong Hyun Yang, 2018, Medical physics.

Wavelet minimum description length detrending for near-infrared spectroscopy.

Sungho Tak, Jong Chul Ye, Yong Jeong, 2009, Journal of biomedical optics.

Image Reconstruction is a New Frontier of Machine Learning

Jeffrey A. Fessler, Klaus Mueller, Ge Wang, 2018, IEEE Transactions on Medical Imaging.

A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction

Jong Chul Ye, Junhong Min, Eunhee Kang, 2016, Medical physics.

Cone-Angle Artifact Removal Using Differentiated Backprojection Domain Deep Learning

Jong Chul Ye, Yoseob Han, Junyoung Kim, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Framelet denoising for low-dose CT using deep learning

Jong Chul Ye, Eunhee Kang, J. C. Ye, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Diffusion Posterior Sampling for General Noisy Inverse Problems

Michael T. McCann, J. C. Ye, M. Klasky, 2022, ICLR.

Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models

J. C. Ye, Hyungjin Chung, Minyoung Park, 2023, ArXiv.

Computational MRI: Compressive Sensing and Beyond

J. C. Ye, L. Ying, M. Doneva, 2020 .

Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks

Jaejun Yoo, Sungho Tak, Jong Chul Ye, 2018, IEEE Transactions on Biomedical Engineering.

AIM 2020 Challenge on Learned Image Signal Processing Pipeline pdf

Radu Timofte, Ruimao Zhang, Kai Li, 2020, ECCV Workshops.

DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging Using Deep Learning

Jong Chul Ye, Yongki Lee, DongHun Ryu, 2020, IEEE Transactions on Medical Imaging.

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-Space Deep Learning for Accelerated MRI

Jong Chul Ye, Yoseob Han, J. C. Ye, 2020, IEEE Transactions on Medical Imaging.

AdaIN-Switchable CycleGAN for Efficient Unsupervised Low-Dose CT Denoising pdf

Jong Chul Ye, Jawook Gu, J. C. Ye, 2020, ArXiv.

Computational MRI: Compressive Sensing and Beyond [From the Guest Editors]

Mariya Doneva, Jong Chul Ye, Leslie Ying, 2020, IEEE Signal Process. Mag..

Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis

Jong Beom Ra, Jong Chul Ye, Yoram Bresler, 2015, Physics in medicine and biology.

PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal Processing

J. C. Ye, Byung-Hoon Kim, Joonyoung Song, 2021, ECCV Workshops.

Annihilating Filter-Based Low-Rank Hankel Matrix Approach for Image Inpainting

Jong Chul Ye, Kyong Hwan Jin, J. C. Ye, 2015, IEEE Transactions on Image Processing.

CycleMorph: Cycle Consistent Unsupervised Deformable Image Registration pdf

Jong Chul Ye, Jieun Kim, Dong Hwan Kim, 2020, Medical Image Anal..

Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty

Jong Chul Ye, Quanzheng Li, Georges El Fakhri, 2015, IEEE Transactions on Medical Imaging.

Neuroelectromagnetic imaging of correlated sources using a novel subspace penalized sparse learning

Jong Chul Ye, Chang-Hwan Im, Jong Min Kim, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Tracing the evolution of multi-scale functional networks in a mouse model of depression using persistent brain network homology

Moo K. Chung, Jong Chul Ye, J. C. Ye, 2014, NeuroImage.

CycleGAN With a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry

Jong Chul Ye, Byeongsu Sim, Sungjun Lim, 2019, IEEE Transactions on Computational Imaging.

Nouvelles directions en habitats intelligents pour la santé

Norbert Noury, Jacques Demongeot, J. C. Ye, 2003 .

Fully iterative scatter corrected digital breast tomosynthesis using GPU-based fast Monte Carlo simulation and composition ratio update.

Jong Chul Ye, Kwang Eun Jang, Kyungsang Kim, 2015, Medical physics.

Sparse SPM : Sparse-Dictionary Learning for Resting-state Functional Connectivity MRI Analysis

Jeonghyeon Lee, Sungho Tak, Jong Chul Ye, 2015 .

Sparse dictionary learning for resting-state fMRI analysis

Kangjoo Lee, Jong Chul Ye, J. C. Ye, 2011, Optical Engineering + Applications.

A self-referencing level-set method for image reconstruction from sparse Fourier samples

Pierre Moulin, Jong Chul Ye, Yoram Bresler, 2001, Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision.

A data-driven spatially adaptive sparse generalized linear model for functional MRI analysis

Sungho Tak, Kangjoo Lee, Jong Chul Ye, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Asymptotic Global Confidence Regions for 3-D Parametric Shape Estimation in Inverse Problems

Pierre Moulin, Jong Chul Ye, Yoram Bresler, 2005, IEEE Transactions on Image Processing.

Motion estimated and compensated compressed sensing dynamic magnetic resonance imaging: What we can learn from video compression techniques

Jong Chul Ye, Hong Jung, J. C. Ye, 2010, Int. J. Imaging Syst. Technol..

Performance evaluation of accelerated functional MRI acquisition using compressed sensing

Jong Chul Ye, Hong Jung, J. C. Ye, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Motion Adaptive Patch-Based Low-Rank Approach for Compressed Sensing Cardiac Cine MRI

Jong Chul Ye, Yoram Bresler, Daniel Kim, 2014, IEEE Transactions on Medical Imaging.

A Data-Driven Sparse GLM for fMRI Analysis Using Sparse Dictionary Learning With MDL Criterion

Sungho Tak, Kangjoo Lee, Jong Chul Ye, 2011, IEEE Transactions on Medical Imaging.

Ultra-Fast Hybrid CPU–GPU Multiple Scatter Simulation for 3-D PET

Jong Beom Ra, Jong Chul Ye, Zang-Hee Cho, 2014, IEEE Journal of Biomedical and Health Informatics.

Unified Theory for Recovery of Sparse Signals in a General Transform Domain

Yanjun Li, Jong Chul Ye, Kyong Hwan Jin, 2016, IEEE Transactions on Information Theory.

AdaIN-Based Tunable CycleGAN for Efficient Unsupervised Low-Dose CT Denoising

Jong Chul Ye, Jawook Gu, J. C. Ye, 2021, IEEE Transactions on Computational Imaging.

Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems

Jong Chul Ye, Yoseob Han, Eunju Cha, 2017, SIAM J. Imaging Sci..

Mumford–Shah Loss Functional for Image Segmentation With Deep Learning

Jong Chul Ye, J. C. Ye, Boah Kim, 2019, IEEE Transactions on Image Processing.

Quantitative Analysis of Hemodynamic and Metabolic Changes in Subcortical Vascular Dementia Using Simultaneous Near-infrared Spectroscopy and Fmri Measurements

Sungho Tak, Jong Chul Ye, Kwangsun Yoo, 2022 .

Reconstruction of Multi-contrast MR Images through Deep Learning.

Jong Chul Ye, Yoseob Han, J. C. Ye, 2019, Medical physics.

DR AF T Deep Learning Can Reverse Photon Migration for Diffuse Optical Tomography pdf

Jong Chul Ye, Abdul Wahab, Young-Wook Choi, 2017 .

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results

Yandong Guo, Jaihyun Park, Tong Yang, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Optimal Transport Driven CycleGAN for Unsupervised Learning in Inverse Problems

Jong Chul Ye, Gyutaek Oh, Byeongsu Sim, 2019, SIAM J. Imaging Sci..

Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems

J. C. Ye, Byeongsu Sim, Gyutaek Oh, 2019, ArXiv.

Grid-Free Localization Algorithm Using Low-Rank Hankel Matrix for Super-Resolution Microscopy

Jong Chul Ye, Michael Unser, Kyong Hwan Jin, 2018, IEEE Transactions on Image Processing.

3D high-density localization microscopy using hybrid astigmatic/ biplane imaging and sparse image reconstruction.

Suliana Manley, Jong Chul Ye, Michael Unser, 2014, Biomedical optics express.

Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis

J. C. Ye, Byung-Hoon Kim, 2020, Frontiers in Neuroscience.

Compressed sensing MRI: a review from signal processing perspective

Jong Chul Ye, J. C. Ye, 2019, BMC biomedical engineering.

Cramer-Rao bounds for parametric shape estimation

Pierre Moulin, Jong Chul Ye, Yoram Bresler, 2002, Proceedings. International Conference on Image Processing.

Bayesian optical diffusion imaging

Charles A. Bouman, Rick P. Millane, Kevin J. Webb, 1999, Optics & Photonics.

Phase Aberration Robust Beamformer for Planewave US Using Self-Supervised Learning

J. C. Ye, Shujaat Khan, Jaeyoung Huh, 2022, ArXiv.

Switchable Deep Beamformer pdf

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2020, ArXiv.

OT-driven Multi-Domain Unsupervised Ultrasound Image Artifact Removal using a Single CNN pdf

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2020, ArXiv.

Universal Plane-Wave Compounding for High Quality US Imaging Using Deep Learning

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2019, 2019 IEEE International Ultrasonics Symposium (IUS).

Compressed sensing metal artifact removal in dental CT

Jong Chul Ye, Jiyoung Choi, Min Woo Kim, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Metal artifact reduction in CT by identifying missing data hidden in metals.

Jin Keun Seo, Jong Chul Ye, Jae Kyu Choi, 2013, Journal of X-ray science and technology.

Score-based Diffusion Models for Bayesian Image Reconstruction

Michael T. McCann, J. C. Ye, M. Klasky, 2023, 2305.16482.

Two-Dimensional Elastic Scattering Coefficients and Enhancement of Nearly Elastic Cloaking

J. C. Ye, H. Ammari, G. Hu, 2017, Journal of Elasticity.

Two-Dimensional Elastic Scattering Coefficients and Enhancement of Nearly Elastic Cloaking

Jong Chul Ye, Habib Ammari, Abdul Wahab, 2016, 1606.08070.

Deep Learning Diffuse Optical Tomography

Jaejun Yoo, Jong Chul Ye, Young-Wook Choi, 2017, IEEE Transactions on Medical Imaging.

Which Contrast Does Matter? Towards a Deep Understanding of MR Contrast using Collaborative GAN pdf

Jong Chul Ye, Dongwook Lee, Won-Jin Moon, 2019, ArXiv.

Adaptive and Compressive Beamforming Using Deep Learning for Medical Ultrasound

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2019, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

Machine Learning for Medical Image Reconstruction: Third International Workshop, MLMIR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings

Jong Chul Ye, Tobias Würfl, Patricia Johnson, 2020, MLMIR@MICCAI.

Medical ultrasound image speckle reduction and resolution enhancement using texture compensated multi-resolution convolution neural network

J. C. Ye, M. Moinuddin, U. Al-Saggaf, 2022, Frontiers in Physiology.

Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems

J. C. Ye, Yoseob Han, YE Jongchul, 2017, SIAM J. Imaging Sci..

Recent progresses of accelerated MRI using annihilating filter-based low-rank interpolation

Jong Chul Ye, Kyong Hwan Jin, Dongwook Lee, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2017, IEEE Transactions on Medical Imaging.

Belief propagation for joint sparse recovery pdf

Jong Chul Ye, Bang Chul Jung, Jongmin Kim, 2011, ArXiv.

Compressive MUSIC: Revisiting the Link Between Compressive Sensing and Array Signal Processing

Jong Chul Ye, Jongmin Kim, J. C. Ye, 2012, IEEE Transactions on Information Theory.

CollaGAN: Collaborative GAN for Missing Image Data Imputation

J. C. Ye, Dongwook Lee, Junyoung Kim, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Deep Learning Interior Tomography for Region-of-Interest Reconstruction pdf

Jong Chul Ye, Yoseob Han, Jawook Gu, 2017, ArXiv.

Reference‐free single‐pass EPI Nyquist ghost correction using annihilating filter‐based low rank Hankel matrix (ALOHA)

Jong Chul Ye, Kyong Hwan Jin, J. C. Ye, 2016, Magnetic resonance in medicine.

Unsupervised Learning for Compressed Sensing MRI Using Cyclegan

Jong Chul Ye, Gyutaek Oh, Byeongsu Sim, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

k-Space Deep Learning for Accelerated MRI.

J. C. Ye, Yoseob Han, 2018, IEEE transactions on medical imaging.

The Foundations of Computational Imaging: A signal processing perspective

J. C. Ye, W. C. Karl, Charles A. Bouman, 2023, IEEE Signal Processing Magazine.

CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN pdf

Jong Chul Ye, Gyutaek Oh, Hyun-Seo Ahn, 2020, ArXiv.

Unsupervised MR Motion Artifact Deep Learning using Outlier-Rejecting Bootstrap Aggregation pdf

Jong Chul Ye, Gyutaek Oh, Jeong Eun Lee, 2020, ArXiv.

Unpaired Deep Learning for Accelerated MRI Using Optimal Transport Driven CycleGAN

Jong Chul Ye, Gyutaek Oh, Byeongsu Sim, 2020, IEEE Transactions on Computational Imaging.

Deep Convolutional Framelets: A General Deep Learning for Inverse Problems pdf

Jong Chul Ye, Yoseob Han, J. C. Ye, 2017, ArXiv.

Compressive dynamic aperture B-mode ultrasound imaging using annihilating filter-based low-rank interpolation

Jong Chul Ye, Kyong Hwan Jin, Yoseob Han, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Compressive Sampling using Structured Low-Rank Interpolation

Jong Chul Ye, Jong Min Kim, Kyong Hwan Jin, 2015 .

A General Framework for Compressed Sensing and Parallel MRI Using Annihilating Filter Based Low-Rank Hankel Matrix

Jong Chul Ye, Kyong Hwan Jin, Dongwook Lee, 2015, IEEE Transactions on Computational Imaging.

Improving M-SBL for Joint Sparse Recovery Using a Subspace Penalty

Jong Chul Ye, Jongmin Kim, Yoram Bresler, 2015, IEEE Transactions on Signal Processing.

Compressed Sensing Shape Estimation of Star-Shaped Objects in Fourier Imaging

Jong Chul Ye, J. C. Ye, 2007, IEEE Signal Processing Letters.

Structured Low-Rank Algorithms: Theory, Magnetic Resonance Applications, and Links to Machine Learning

J. C. Ye, M. Jacob, M. Mani, 2019, IEEE Signal Processing Magazine.

Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction pdf

Jong Chul Ye, Jawook Gu, J. C. Ye, 2017, ArXiv.

Fast live cell imaging at nanometer scale using annihilating filter-based low-rank Hankel matrix approach

Suliana Manley, Jong Chul Ye, Michael Unser, 2015, SPIE Optical Engineering + Applications.

DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval pdf

Jong Chul Ye, Eunju Cha, J. C. Ye, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Compressive subspace fitting for multiple measurement vectors

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

Non-iterative exact inverse scattering using simultaneous orthogonal matching pursuit (S-OMP)

Jong Chul Ye, Su Yeon Lee, J. C. Ye, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Noise Robust Joint Sparse Recovery using Compressive Subspace Fitting pdf

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2011, ArXiv.

Group sparse dictionary learning and inference for resting-state fMRI analysis of Alzheimer'S disease

Jeonghyeon Lee, Jong Chul Ye, Yong Jeong, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Resting-state fMRI analysis of Alzheimer's disease progress using sparse dictionary learning

Jeonghyeon Lee, Jong Chul Ye, J. C. Ye, 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Statistical parametric mapping of FMRI data using sparse dictionary learning

Kangjoo Lee, Jong Chul Ye, J. C. Ye, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Compressive MUSIC: A Missing Link Between Compressive Sensing and Array Signal Processing pdf

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2010, ArXiv.

Wavelet Residual Network for Low-Dose CT via Deep Convolutional Framelets pdf

Jong Chul Ye, Jae Jun Yoo, Eunhee Kang, 2017, ArXiv.

Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction pdf

Jong Chul Ye, Junhong Min, Eunhee Kang, 2017, ArXiv.

Globally convergent 3D dynamic PET reconstruction with patch-based non-convex low rank regularization

Jong Beom Ra, Jong Chul Ye, Zang-Hee Cho, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

k‐Space deep learning for reference‐free EPI ghost correction

Jong Chul Ye, Yoseob Han, Juyoung Lee, 2018, Magnetic resonance in medicine.

MRI artifact correction using sparse + low‐rank decomposition of annihilating filter‐based hankel matrix

Jong Chul Ye, Kyong Hwan Jin, Dongwook Lee, 2017, Magnetic resonance in medicine.

Sparse SPM: Group Sparse-dictionary learning in SPM framework for resting-state functional connectivity MRI analysis

Sang Won Seo, Young-Beom Lee, Jeonghyeon Lee, 2016, NeuroImage.

Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution

Jong Chul Ye, Hyungjin Chung, Eung Yeop Kim, 2020, IEEE Transactions on Medical Imaging.

Deep Learning Fast MRI Using Channel Attention in Magnitude Domain

Jong Chul Ye, Joonhyung Lee, J. C. Ye, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Unsupervised Deep Learning for MR Angiography with Flexible Temporal Resolution pdf

Jong Chul Ye, Hyungjin Chung, Eung Yeop Kim, 2020, ArXiv.

Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction

Jong Chul Ye, Gyutaek Oh, Eunju Cha, 2020, IEEE Journal of Selected Topics in Signal Processing.

Boosting CNN beyond Label in Inverse Problems pdf

Jong Chul Ye, Eunha Lee, Eunju Cha, 2019, ArXiv.

k-Space Deep Learning for Parallel MRI: Application to Time-Resolved MR Angiography pdf

Jong Chul Ye, Eung-Yeop Kim, Eunju Cha, 2018, ArXiv.

Effect of the “∇D” Term in Optical Diffusion Imaging

J. C. Ye, K. Webb, R. Millane, 1998, Signal Recovery and Synthesis.

Relaxation time constants and apparent diffusion coefficients of rat retina at 7 Tesla

J. C. Ye, Hong Jung, 2010 .

3D macromolecule structure reconstruction from electron micrograph by exploiting symmetry and sparsity

Jong Chul Ye, Jiyoung Choi, Min Woo Kim, 2008, Electronic Imaging.

Lipschitz-Killing curvature based expected Euler characteristics for p-value correction in fNIRS

Sungho Tak, Jong Chul Ye, J. C. Ye, 2012, Journal of Neuroscience Methods.

Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models

J. C. Ye, Hyungjin Chung, Minyoung Park, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

High-speed terahertz reflection three-dimensional imaging using beam steering.

Jong Chul Ye, Kyong Hwan Jin, J. C. Ye, 2015, Optics express.

Multi-view optical tomography using L1 data fidelity and sparsity constraint

Jong Chul Ye, J. C. Ye, Jaeduck Jang, 2008, SPIE BiOS.

BMC Biomedical Engineering: a home for all biomedical engineering research

J. C. Ye, D. Zeugolis, A. Lefor, 2019, BMC biomedical engineering.

Improved k–t BLAST and k–t SENSE using FOCUSS

J. C. Ye, Hong Jung, E. Kim, 2007, Physics in medicine and biology.

Deep Learning with Domain Adaptation for Accelerated Projection Reconstruction MR

J. C. Ye, J. Yoo, Yoseob Han, 2017, ArXiv.

Machine Learning for Medical Image Reconstruction: Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

Daniel Rueckert, Jong Chul Ye, Florian Knoll, 2019, MLMIR@MICCAI.

Compressed sensing fMRI using gradient-recalled echo and EPI sequences

Jong Chul Ye, Xiaopeng Zong, Seong-Gi Kim, 2014, NeuroImage.

1 Compressed sensing fMRI using gradient-recalled echo and

Jong Chul Ye, Seong-Gi Kim, Alexander John Poplawsky, 2014 .

Deep Learning Reconstruction for 9-View Dual Energy CT Baggage Scanner pdf

Jong Chul Ye, Yoseob Han, Jingu Kang, 2018, ArXiv.

Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpus pdf

Joon Beom Seo, Jong Chul Ye, Sang Min Lee, 2021, ArXiv.

High Resolution Time Resolved Contrast Enhanced MR Angiography Using k-t FOCUSS

Jong Chul Ye, Hong Jung, Eung Yeop Kim, 2010 .

Cryo-electron microscopy single particle reconstruction of virus particles using compressed sensing theory

Liu Yu, Jong Chul Ye, Jiyoung Choi, 2007, Electronic Imaging.

Deep Learning Diffuse Optical Tomography

J. C. Ye, Jaejun Yoo, D. Heo, 2017, IEEE Transactions on Medical Imaging.

Sampling scheme optimization for diffuse optical tomography based on data and image space rankings

Changhwan Kim, Jong Chul Ye, Seungryong Cho, 2016, Journal of biomedical optics.

Beyond Born-Rytov limit for super-resolution optical diffraction tomography.

Jong Chul Ye, Abdul Wahab, YongKeun Park, 2017, Optics express.

Deep Learning for Accelerated Ultrasound Imaging

Jong Chul Ye, J. C. Ye, Yeo Hun Yoon, 2017, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Joint Sparse Recovery Framework for Accurate Reconstruction of Inclusions in Elastic Media

Jong Chul Ye, Abdul Wahab, Mikyoung Lim, 2016, SIAM J. Imaging Sci..

Joint sparsity-driven non-iterative simultaneous reconstruction of absorption and scattering in diffuse optical tomography.

J. C. Ye, O. Lee, 2013, Optics Express.

Compressive Diffuse Optical Tomography: Noniterative Exact Reconstruction Using Joint Sparsity

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2011, IEEE Transactions on Medical Imaging.

Exact reconstruction formula for diffuse optical tomography using simultaneous sparse representation

Jong Chul Ye, Yoram Bresler, Su Yeon Lee, 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Joint sparse recovery in inverse scattering

Jong Chul Ye, Okkyun Lee, J. C. Ye, 2015, SPIE Optical Engineering + Applications.

Joint sparsity recovery method for the EIT problem to reconstruct anomalies

Jong Chul Ye, Ok Kyun Lee, Hyeonbae Kang, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Accurate inversion of absorption and scattering in diffuse optical tomography without iterative Green's function update

Jong Chul Ye, Ok Kyun Lee, J. C. Ye, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Improving Noise Robustness in Subspace-Based Joint Sparse Recovery

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2011, IEEE Transactions on Signal Processing.

A Mathematical Framework for Deep Learning in Elastic Source Imaging

Jong Chul Ye, Abdul Wahab, Jae Jun Yoo, 2018, SIAM J. Appl. Math..

Quantitative susceptibility map reconstruction using annihilating filter‐based low‐rank Hankel matrix approach

Jong Chul Ye, Hyun-Seo Ahn, Sunghong Park, 2018, Magnetic resonance in medicine.

Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems

J. C. Ye, P. Maass, Alexander Denker, 2023, ArXiv.

Universal Deep Beamformer for Variable Rate Ultrasound Imaging pdf

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2019, ArXiv.

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-Space Deep Learning for Accelerated MRI

J. C. Ye, Yoseob Han, 2018, IEEE Transactions on Medical Imaging.

Unsupervised Deconvolution Neural Network for High Quality Ultrasound Imaging

Jong Chul Ye, Shujaat Khan, Jaeyoung Huh, 2020, 2020 IEEE International Ultrasonics Symposium (IUS).

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

Sungho Tak, Jong Chul Ye, Yong Jeong, 2008, SPIE BiOS.

Wavelet minimum description length detrending for near-infrared spectroscopy.

J. C. Ye, S. Tak, Y. Jeong, 2009, Journal of Biomedical Optics.

Lipschitz-Killing curvature based expected Euler characteristics for p-value correction in fNIRS

J. C. Ye, S. Tak, Hua Li, 2012, Journal of Neuroscience Methods.

Quantitative analysis of hemodynamic and metabolic changes in subcortical vascular dementia using simultaneous near-infrared spectroscopy and fMRI measurements

J. C. Ye, S. Tak, Y. Jeong, 2011, NeuroImage.

Continuous Conversion of CT Kernel Using Switchable CycleGAN With AdaIN

Jong Chul Ye, Eung Yeop Kim, Serin Yang, 2020, IEEE Transactions on Medical Imaging.

Hemispheric asymmetry in hand preference of right-handers for passive vibrotactile perception: an fNIRS study

J. C. Ye, S. Tak, Jinwook Jung, 2020, Scientific Reports.

Improving the Reliability of Pharmacokinetic Parameters at Dynamic Contrast-enhanced MRI in Astrocytomas: A Deep Learning Approach.

J. C. Ye, B. Jeong, Yoseob Han, 2020, Radiology.

Reference-free EPI Nyquist ghost correction using annihilating filter-based low rank hankel matrix for K-space interpolation

Jong Chul Ye, Kyong Hwan Jin, Juyoung Lee, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Sparse and low-rank decomposition of MR artifact images using annihilating filter-based Hankel matrix

Jong Chul Ye, Kyong Hwan Jin, Dongwook Lee, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Dynamic sparse support tracking with multiple measurement vectors using compressive MUSIC

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Exact Dynamic Support Tracking with Multiple Measurement Vectors using Compressive MUSIC pdf

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2011, ArXiv.

Coherent source imaging and dynamic support tracking for inverse scattering using compressive MUSIC

Jong Chul Ye, Okkyun Lee, Jong Min Kim, 2011, Optical Engineering + Applications.

Compressive MUSIC with optimized partial support for joint sparse recovery

Jong Chul Ye, Jongmin Kim, Ok Kyun Lee, 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

Accuracy improvement of quantification information using super-resolution with convolutional neural network for microscopy images

Myoung-Hee Kim, Jong Chul Ye, Sejung Yang, 2020, Biomed. Signal Process. Control..

Single channel blind image deconvolution from radially symmetric blur kernels.

Jong Chul Ye, Kwang Eun Jang, J. C. Ye, 2007, Optics express.

Unsupervised Deformable Image Registration Using Cycle-Consistent CNN pdf

Jong Chul Ye, Dong Hwan Kim, Seong Ho Park, 2019, MICCAI.

Sparse SPM: Group Sparse-dictionary learning in SPM framework for resting-state functional connectivity MRI analysis

J. C. Ye, S. Tak, Y. Jeong, 2016, NeuroImage.

Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non-EPI fMRI at 9.4T

Jong Chul Ye, Seong-Gi Kim, Sung-Hong Park, 2015, BioMed research international.

Coherent optical computing for T-ray imaging.

Kanghee Lee, Jong Chul Ye, Jaewook Ahn, 2010, Optics letters.

Diagnosis of coronary layered plaque by deep learning

J. C. Ye, I. Jang, A. Nakajima, 2023, Scientific Reports.

In vivo optical molecular imaging: principles and signal processing issues

Charles A. Bouman, Jong Chul Ye, Rick P. Millane, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..