250 citations · 2.3k across the 66 of their papers we have counts for
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DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging using Deep Learning
DongHun Ryu, Dongmin Ryu, YoonSeok Baek +8
Optical diffraction tomography measures the three-dimensional refractive index map of a specimen and visualizes biochemical phenomena at the nanoscale in a non-destructive manner.…
Calibration-free quantitative phase imaging using data-driven aberration modeling
Taean Chang, Youngju Jo, Gunho Choi +3
We present a data-driven approach to compensate for optical aberration in calibration-free quantitative phase imaging (QPI). Unlike existing methods that require additional measure…
Computational Approach to Dark-Field Optical Diffraction Tomography
Taean Chang, Seungwoo Shin, Moosung Lee +1
The measurement of three-dimensional (3D) images and the analysis of subcellular organelles are crucial for the study of the pathophysiology of cells and tissues. Optical diffracti…
Deep learning-enabled image quality control in tomographic reconstruction: Robust optical diffraction tomography
Donghun Ryu, Youngju Jo, Jihyeong Yoo +6
In tomographic reconstruction, the image quality of the reconstructed images can be significantly degraded by defects in the measured two-dimensional (2D) raw image data. Despite t…