71 citations · 219 across the 6 of their papers we have counts for
6 papers
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…
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…
Deep learning approach to coherent noise reduction in optical diffraction tomography
Gunho Choi, Donghun Ryu, Youngju Jo +4
We present a deep neural network to reduce coherent noise in three-dimensional quantitative phase imaging. Inspired by the cycle generative adversarial network, the denoising netwo…
Quantitative Phase Imaging and Artificial Intelligence: A Review
YoungJu Jo, Hyungjoo Cho, Sang Yun Lee +4
Recent advances in quantitative phase imaging (QPI) and artificial intelligence (AI) have opened up the possibility of an exciting frontier. The fast and label-free nature of QPI e…
Collaborative effects of wavefront shaping and optical clearing agent in optical coherence tomography
Hyeonseung Yu, Peter Lee, YoungJu Jo +4
We demonstrate that simultaneous application of optical clearing agents (OCAs) and complex wavefront shaping in optical coherence tomography (OCT) can provide significant enhanceme…
Label-free identification of individual bacteria using Fourier transform light scattering
YoungJu Jo, JaeHwang Jung, Min-hyeok Kim +3
Rapid identification of bacterial species is crucial in medicine and food hygiene. In order to achieve rapid and label-free identification of bacterial species at the single bacter…