133 citations · 342 across the 19 of their papers we have counts for
4 papers · 1 filter
BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization
Il Yong Chun, Xuehang Zheng, Yong Long +1
Obtaining accurate and reliable images from low-dose computed tomography (CT) is challenging. Regression convolutional neural network (CNN) models that are learned from training da…
Momentum-Net: Fast and convergent iterative neural network for inverse problems
Il Yong Chun, Zhengyu Huang, Hongki Lim +1
Iterative neural networks (INN) are rapidly gaining attention for solving inverse problems in imaging, image processing, and computer vision. INNs combine regression NNs and an ite…
Improved low-count quantitative PET reconstruction with an iterative neural network
Hongki Lim, Il Yong Chun, Yuni K. Dewaraja +1
Image reconstruction in low-count PET is particularly challenging because gammas from natural radioactivity in Lu-based crystals cause high random fractions that lower the measurem…
Convolutional Analysis Operator Learning: Dependence on Training Data
Il Yong Chun, David Hong, Ben Adcock +1
Convolutional analysis operator learning (CAOL) enables the unsupervised training of (hierarchical) convolutional sparsifying operators or autoencoders from large datasets. One can…