1 citations · 1 across the 3 of their papers we have counts for
3 papers
eess.IV2024
Fast and accurate sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization
Heejun Shin, Taehee Kim, Jongho Lee +3
Cone beam computed tomography (CBCT) is an emerging medical imaging technique to visualize the internal anatomical structures of patients. During a CBCT scan, several projection im…
eess.IV2022
Self-supervised training of deep denoisers in multi-coil MRI considering noise correlations
Juhyung Park, Dongwon Park, Sooyeon Ji +3
Deep learning-based denoising methods have shown powerful results for improving the signal-to-noise ratio of magnetic resonance (MR) images, mostly by leveraging supervised learnin…
eess.IV2022★ 1 cited
Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging
Il Yong Chun, Dongwon Park, Xuehang Zheng +2
Regression that predicts continuous quantity is a central part of applications using computational imaging and computer vision technologies. Yet, studying and understanding self-su…