716 citations · 2.8k across the 74 of their papers we have counts for
20 papers · 1 filter
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…
DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging using Deep Learning
DongHun Ryu, Dongmin Ryu, YoonSeok Baek +8
Optical diffraction tomography measures the three-dimensional refractive index map of a specimen and visualizes biochemical phenomena at the nanoscale in a non-destructive manner.…