2.6k citations · 3.7k across the 10 of their papers we have counts for
14 papers
Learning Local Implicit Fourier Representation for Image Warping
Jaewon Lee, Kwang Pyo Choi, Kyong Hwan Jin
Image warping aims to reshape images defined on rectangular grids into arbitrary shapes. Recently, implicit neural functions have shown remarkable performances in representing imag…
Local Texture Estimator for Implicit Representation Function
Jaewon Lee, Kyong Hwan Jin
Recent works with an implicit neural function shed light on representing images in arbitrary resolution. However, a standalone multi-layer perceptron shows limited performance in l…
Reducing the Human Effort in Developing PET-CT Registration
Teaghan O'Briain, Kyong Hwan Jin, Hongyoon Choi +3
We aim to reduce the tedious nature of developing and evaluating methods for aligning PET-CT scans from multiple patient visits. Current methods for registration rely on correspond…
Time-Dependent Deep Image Prior for Dynamic MRI
Jaejun Yoo, Kyong Hwan Jin, Harshit Gupta +3
We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study…
Self-Supervised Deep Active Accelerated MRI
Kyong Hwan Jin, Michael Unser, Kwang Moo Yi
We propose to simultaneously learn to sample and reconstruct magnetic resonance images (MRI) to maximize the reconstruction quality given a limited sample budget, in a self-supervi…
Direct Reconstruction of Saturated Samples in Band-Limited OFDM Signals
Kyong Hwan Jin, Gain Kim, Yusuf Leblebici +2
Given a set of samples, a few of them being possibly saturated, we propose an efficient algorithm in order to cancel saturation while reconstructing band-limited signals. Our metho…
A Review of Convolutional Neural Networks for Inverse Problems in Imaging
Michael T. McCann, Kyong Hwan Jin, Michael Unser
In this survey paper, we review recent uses of convolution neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large…
CNN-Based Projected Gradient Descent for Consistent Image Reconstruction
Harshit Gupta, Kyong Hwan Jin, Ha Q. Nguyen +2
We present a new method for image reconstruction which replaces the projector in a projected gradient descent (PGD) with a convolutional neural network (CNN). CNNs trained as high-…
Predicting Cognitive Decline with Deep Learning of Brain Metabolism and Amyloid Imaging
Hongyoon Choi, Kyong Hwan Jin
For effective treatment of Alzheimer disease (AD), it is important to identify subjects who are most likely to exhibit rapid cognitive decline. Herein, we developed a novel framewo…
Unified Theory for Recovery of Sparse Signals in a General Transform Domain
Kiryung Lee, Yanjun Li, Kyong Hwan Jin +1
Compressed sensing provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that practical algorithms provide robust recovery from noisy linear measur…
Deep Convolutional Neural Network for Inverse Problems in Imaging
Kyong Hwan Jin, Michael T. McCann, Emmanuel Froustey +1
In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as t…
Compressive Sampling using Annihilating Filter-based Low-Rank Interpolation
Jong Chul Ye, Jong Min Kim, Kyong Hwan Jin +1
While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist limit in recovering sparse signals, a solution approach usually takes a form of invers…
Sparse + Low Rank Decomposition of Annihilating Filter-based Hankel Matrix for Impulse Noise Removal
Kyong Hwan Jin, Jong Chul Ye
Recently, so called annihilating filer-based low rank Hankel matrix (ALOHA) approach was proposed as a powerful image inpainting method. Based on the observation that smoothness or…
A general framework for compressed sensing and parallel MRI using annihilating filter based low-rank Hankel matrix
Kyong Hwan Jin, Dongwook Lee, Jong Chul Ye
Parallel MRI (pMRI) and compressed sensing MRI (CS-MRI) have been considered as two distinct reconstruction problems. Inspired by recent k-space interpolation methods, an annihilat…