20 citations · 50 across the 4 of their papers we have counts for
7 papers
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal
Yoseob Han, Junyoung Kim, Jong Chul Ye
Conebeam CT using a circular trajectory is quite often used for various applications due to its relative simple geometry. For conebeam geometry, Feldkamp, Davis and Kress algorithm…
One Network to Solve All ROIs: Deep Learning CT for Any ROI using Differentiated Backprojection
Yoseob Han, Jong Chul Ye
Computed tomography for region-of-interest (ROI) reconstruction has advantages of reducing X-ray radiation dose and using a small detector. However, standard analytic reconstructio…
k-Space Deep Learning for Reference-free EPI Ghost Correction
Juyoung Lee, Yoseob Han, Jae-Kyun Ryu +2
Nyquist ghost artifacts in EPI are originated from phase mismatch between the even and odd echoes. However, conventional correction methods using reference scans often produce erro…
Deep Learning Reconstruction for 9-View Dual Energy CT Baggage Scanner
Yoseob Han, Jingu Kang, Jong Chul Ye
For homeland and transportation security applications, 2D X-ray explosive detection system (EDS) have been widely used, but they have limitations in recognizing 3D shape of the hid…
Deep Learning Interior Tomography for Region-of-Interest Reconstruction
Yoseob Han, Jawook Gu, Jong Chul Ye
Interior tomography for the region-of-interest (ROI) imaging has advantages of using a small detector and reducing X-ray radiation dose. However, standard analytic reconstruction s…