74 citations · 84 across the 15 of their papers we have counts for
16 papers
MAGIC: Few-Shot Mask-Guided Anomaly Inpainting with Prompt Perturbation, Spatially Adaptive Guidance, and Context Awareness
JaeHyuck Choi, MinJun Kim, Je Hyeong Hong
Few-shot anomaly generation is a key challenge in industrial quality control. Although diffusion models are promising, existing methods struggle: global prompt-guided approaches co…
Restoration Guarantee of Image Inpainting via Low Rank Patch Matrix Completion
Jian-Feng Cai, Jae Kyu Choi, Jingyang Li +1
In recent years, patch-based image restoration approaches have demonstrated superior performance compared to conventional variational methods. This paper delves into the mathematic…
Approximation Theory of Wavelet Frame Based Image Restoration
Jian-Feng Cai, Jae Kyu Choi, Jianbin Yang
In this paper, we analyze the error estimate of a wavelet frame based image restoration method from degraded and incomplete measurements. We present the error between the underlyin…
Two Stage Continuous Domain Regularization for Piecewise Constant Image Restoration
Jian-Feng Cai, Jae Kyu Choi, Chenchuan Zhou
The finite-rate-of-innovation (FRI) framework which corresponds a signal/image to a structured low-rank matrix is emerging as an alternative to the traditional sparse regularizatio…
Approximation Theory of Total Variation Minimization for Data Completion
Jian-Feng Cai, Jae Kyu Choi, Ke Wei
Total variation (TV) minimization is one of the most important techniques in modern signal/image processing, and has wide range of applications. While there are numerous recent wor…
Image Restoration: Structured Low Rank Matrix Framework for Piecewise Smooth Functions and Beyond
Jian-Feng Cai, Jae Kyu Choi, Jingyang Li +1
Recently, mapping a signal/image into a low rank Hankel/Toeplitz matrix has become an emerging alternative to the traditional sparse regularization, due to its ability to alleviate…
Data Driven Tight Frame for Compressed Sensing MRI Reconstruction via Off-the-Grid Regularization
Jian-Feng Cai, Jae Kyu Choi, Ke Wei
Recently, the finite-rate-of-innovation (FRI) based continuous domain regularization is emerging as an alternative to the conventional on-the-grid sparse regularization for the com…
Framelet Pooling Aided Deep Learning Network : The Method to Process High Dimensional Medical Data
Chang Min Hyun, Kang Cheol Kim, Hyun Cheol Cho +2
Machine learning-based analysis of medical images often faces several hurdles, such as the lack of training data, the curse of dimensionality problem, and the generalization issues…
Unpaired image denoising using a generative adversarial network in X-ray CT
Hyoung Suk Park, Jineon Baek, Sun Kyoung You +2
This paper proposes a deep learning-based denoising method for noisy low-dose computerized tomography (CT) images in the absence of paired training data. The proposed method uses a…
NLTG Priors in Medical Image: Nonlocal TV-Gaussian (NLTG) prior for Bayesian inverse problems with applications to Limited CT Reconstruction
Didi Lv, Qingping Zhou, Jae Kyu Choi +2
Bayesian inference methods have been widely applied in inverse problems, {largely due to their ability to characterize the uncertainty associated with the estimation results.} {In…
Whole Brain Susceptibility Mapping Using Harmonic Incompatibility Removal
Chenglong Bao, Jae Kyu Choi, Bin Dong
Quantitative susceptibility mapping (QSM) aims to visualize the three dimensional susceptibility distribution by solving the field-to-source inverse problem using the phase data in…
PET-MRI Joint Reconstruction by Joint Sparsity Based Tight Frame Regularization
Jae Kyu Choi, Chenglong Bao, Xiaoqun Zhang
Recent technical advances lead to the coupling of PET and MRI scanners, enabling to acquire functional and anatomical data simultaneously. In this paper, we propose a tight frame b…
An Edge Driven Wavelet Frame Model for Image Restoration
Jae Kyu Choi, Bin Dong, Xiaoqun Zhang
Wavelet frame systems are known to be effective in capturing singularities from noisy and degraded images. In this paper, we introduce a new edge driven wavelet frame model for ima…
Dipole Incompatibility Related Artifacts in Quantitative Susceptibility Mapping
Liangdong Zhou, Jae Kyu Choi, Youngwook Kee +2
Artifacts in quantitative susceptibility mapping (QSM) are analyzed to establish an optimal design criterion for QSM inversion algorithms. The magnetic field data is decomposed int…
Limited Tomography Reconstruction via Tight Frame and Sinogram Extrapolation
Jae Kyu Choi, Bin Dong, Xiaoqun Zhang
X-ray computed tomography (CT) is one of widely used diagnostic tools for medical and dental tomographic imaging of the human body. However, the standard filtered backprojection re…
Characterization of Metal Artifacts in X-ray Computed Tomography
Hyoung Suk Park, Jae Kyu Choi, Jin Keun Seo
Metal streak artifacts in X-ray computerized tomography (CT) are rigorously characterized here using the notion of the wavefront set from microlocal analysis. The metal artifacts a…