20 citations · 50 across the 9 of their papers we have counts for
9 papers
scMamba: A Pre-Trained Model for Single-Nucleus RNA Sequencing Analysis in Neurodegenerative Disorders
Gyutaek Oh, Baekgyu Choi, Seyoung Jin +2
Single-nucleus RNA sequencing (snRNA-seq) has significantly advanced our understanding of the disease etiology of neurodegenerative disorders. However, the low quality of specimens…
scHyena: Foundation Model for Full-Length Single-Cell RNA-Seq Analysis in Brain
Gyutaek Oh, Baekgyu Choi, Inkyung Jung +1
Single-cell RNA sequencing (scRNA-seq) has made significant strides in unraveling the intricate cellular diversity within complex tissues. This is particularly critical in the brai…
Unpaired Deep Learning for Pharmacokinetic Parameter Estimation from Dynamic Contrast-Enhanced MRI
Gyutaek Oh, Won-Jin Moon, Jong Chul Ye
DCE-MRI provides information about vascular permeability and tissue perfusion through the acquisition of pharmacokinetic parameters. However, traditional methods for estimating the…
Annealed Score-Based Diffusion Model for MR Motion Artifact Reduction
Gyutaek Oh, Jeong Eun Lee, Jong Chul Ye
Motion artifact reduction is one of the important research topics in MR imaging, as the motion artifact degrades image quality and makes diagnosis difficult. Recently, many deep le…
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…
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…
Unpaired Deep Learning for Accelerated MRI using Optimal Transport Driven CycleGAN
Gyutaek Oh, Byeongsu Sim, Hyungjin Chung +2
Recently, deep learning approaches for accelerated MRI have been extensively studied thanks to their high performance reconstruction in spite of significantly reduced runtime compl…
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…
Optimal Transport driven CycleGAN for Unsupervised Learning in Inverse Problems
Byeongsu Sim, Gyutaek Oh, Jeongsol Kim +2
To improve the performance of classical generative adversarial network (GAN), Wasserstein generative adversarial networks (W-GAN) was developed as a Kantorovich dual formulation of…