426 citations · 438 across the 6 of their papers we have counts for
6 papers
NeRF Solves Undersampled MRI Reconstruction
Tae Jun Jang, Chang Min Hyun
This article presents a novel undersampled magnetic resonance imaging (MRI) technique that leverages the concept of Neural Radiance Field (NeRF). With radial undersampling, the cor…
Unsupervised sequence-to-sequence learning for automatic signal quality assessment in multi-channel electrical impedance-based hemodynamic monitoring
Chang Min Hyun, Tae-Geun Kim, Kyounghun Lee
This study proposes an unsupervised sequence-to-sequence learning approach that automatically assesses the motion-induced reliability degradation of the cardiac volume signal (CVS)…
Automatic 3D Registration of Dental CBCT and Face Scan Data using 2D Projection Images
Hyoung Suk Park, Chang Min Hyun, Sang-Hwy Lee +2
This paper presents a fully automatic registration method of dental cone-beam computed tomography (CBCT) and face scan data. It can be used for a digital platform of 3D jaw-teeth-f…
Nonlinear ill-posed problem in low-dose dental cone-beam computed tomography
Hyoung Suk Park, Chang Min Hyun, Jin Keun Seo
This paper describes the mathematical structure of the ill-posed nonlinear inverse problem of low-dose dental cone-beam computed tomography (CBCT) and explains the advantages of a…
Machine Learning-based Signal Quality Assessment for Cardiac Volume Monitoring in Electrical Impedance Tomography
Chang Min Hyun, Tae Jun Jang, Jeongchan Nam +3
Owing to recent advances in thoracic electrical impedance tomography, a patient's hemodynamic function can be noninvasively and continuously estimated in real-time by surveilling a…
Deep learning for undersampled MRI reconstruction
Chang Min Hyun, Hwa Pyung Kim, Sung Min Lee +2
This paper presents a deep learning method for faster magnetic resonance imaging (MRI) by reducing k-space data with sub-Nyquist sampling strategies and provides a rationale for wh…