32 citations · 66 across the 6 of their papers we have counts for
11 papers
Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training
Sangjoon Park, Gwanghyun Kim, Jeongsol Kim +2
Federated learning, which shares the weights of the neural network across clients, is gaining attention in the healthcare sector as it enables training on a large corpus of decentr…
Deep Learning for Ultrasound Beamforming
Ruud JG van Sloun, Jong Chul Ye, Yonina C Eldar
Diagnostic imaging plays a critical role in healthcare, serving as a fundamental asset for timely diagnosis, disease staging and management as well as for treatment choice, plannin…
Federated CycleGAN for Privacy-Preserving Image-to-Image Translation
Joonyoung Song, Jong Chul Ye
Unsupervised image-to-image translation methods such as CycleGAN learn to convert images from one domain to another using unpaired training data sets from different domains. Unfort…
Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images
Kwanyoung Kim, Jong Chul Ye
Recently, there has been extensive research interest in training deep networks to denoise images without clean reference. However, the representative approaches such as Noise2Noise…
Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention
Byung-Hoon Kim, Jong Chul Ye, Jae-Jin Kim
Functional connectivity (FC) between regions of the brain can be assessed by the degree of temporal correlation measured with functional neuroimaging modalities. Based on the fact…
Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning
Hyungjin Chung, Jaehyun Kim, Jeong Hee Yoon +2
Diffusion-weighted MRI is nowadays performed routinely due to its prognostic ability, yet the quality of the scans are often unsatisfactory which can subsequently hamper the clinic…