77 citations · 190 across the 4 of their papers we have counts for
4 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 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…
Neural Stain-Style Transfer Learning using GAN for Histopathological Images
Hyungjoo Cho, Sungbin Lim, Gunho Choi +1
Performance of data-driven network for tumor classification varies with stain-style of histopathological images. This article proposes the stain-style transfer (SST) model based on…