54 citations · 54 across the 1 of their papers we have counts for
5 papers
Deep learning-based color holographic microscopy
Tairan Liu, Zhensong Wei, Yair Rivenson +4
We report a framework based on a generative adversarial network (GAN) that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated…
Deep learning-based super-resolution in coherent imaging systems
Tairan Liu, Kevin de Haan, Yair Rivenson +4
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can…
PhaseStain: Digital staining of label-free quantitative phase microscopy images using deep learning
Yair Rivenson, Tairan Liu, Zhensong Wei +2
Using a deep neural network, we demonstrate a digital staining technique, which we term PhaseStain, to transform quantitative phase images (QPI) of labelfree tissue sections into i…
Deep learning-based virtual histology staining using auto-fluorescence of label-free tissue
Yair Rivenson, Hongda Wang, Zhensong Wei +3
Histological analysis of tissue samples is one of the most widely used methods for disease diagnosis. After taking a sample from a patient, it goes through a lengthy and laborious…
Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recovery
Yichen Wu, Yair Rivenson, Yibo Zhang +4
Holography encodes the three dimensional (3D) information of a sample in the form of an intensity-only recording. However, to decode the original sample image from its hologram(s),…