716 citations · 2.8k across the 74 of their papers we have counts for
9 papers · 2 filters
CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN
Gyutaek Oh, Hyokyoung Bae, Hyun-Seo Ahn +2
Quantitative susceptibility mapping (QSM) is a useful magnetic resonance imaging (MRI) technique which provides spatial distribution of magnetic susceptibility values of tissues. Q…
DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval
Eunju Cha, Chanseok Lee, Mooseok Jang +1
Fourier phase retrieval is a classical problem of restoring a signal only from the measured magnitude of its Fourier transform. Although Fienup-type algorithms, which use prior kno…
Unsupervised MR Motion Artifact Deep Learning using Outlier-Rejecting Bootstrap Aggregation
Gyutaek Oh, Jeong Eun Lee, Jong Chul Ye
Recently, deep learning approaches for MR motion artifact correction have been extensively studied. Although these approaches have shown high performance and reduced computational…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
Continuous Conversion of CT Kernel using Switchable CycleGAN with AdaIN
Serin Yang, Eung Yeop Kim, Jong Chul Ye
X-ray computed tomography (CT) uses different filter kernels to highlight different structures. Since the raw sinogram data is usually removed after the reconstruction, in case the…
CycleMorph: Cycle Consistent Unsupervised Deformable Image Registration
Boah Kim, Dong Hwan Kim, Seong Ho Park +3
Image registration is a fundamental task in medical image analysis. Recently, deep learning based image registration methods have been extensively investigated due to their excelle…
Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
Ultrasound (US) imaging is a fast and non-invasive imaging modality which is widely used for real-time clinical imaging applications without concerning about radiation hazard. Unfo…
Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction
Eunju Cha, Gyutaek Oh, Jong Chul Ye
Recently, deep learning approaches have been extensively investigated to reconstruct images from accelerated magnetic resonance image (MRI) acquisition. Although these approaches p…
Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis
Byung-Hoon Kim, Jong Chul Ye
Graph neural networks (GNN) rely on graph operations that include neural network training for various graph related tasks. Recently, several attempts have been made to apply the GN…