2.6k citations · 9.9k across the 41 of their papers we have counts for
8 papers · 1 filter
Spectrally-Encoded Single-Pixel Machine Vision Using Diffractive Networks
Jingxi Li, Deniz Mengu, Nezih T. Yardimci +6
3D engineering of matter has opened up new avenues for designing systems that can perform various computational tasks through light-matter interaction. Here, we demonstrate the des…
Resolution enhancement in scanning electron microscopy using deep learning
Kevin de Haan, Zachary S. Ballard, Yair Rivenson +2
We report resolution enhancement in scanning electron microscopy (SEM) images using a generative adversarial network. We demonstrate the veracity of this deep learning-based super-…
Three-dimensional virtual refocusing of fluorescence microscopy images using deep learning
Yichen Wu, Yair Rivenson, Hongda Wang +5
Three-dimensional (3D) fluorescence microscopy in general requires axial scanning to capture images of a sample at different planes. Here we demonstrate that a deep convolutional n…
Cross-modality deep learning brings bright-field microscopy contrast to holography
Yichen Wu, Yilin Luo, Gunvant Chaudhari +4
Deep learning brings bright-field microscopy contrast to holographic images of a sample volume, bridging the volumetric imaging capability of holography with the speckle- and artif…
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…
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),…
Phase recovery and holographic image reconstruction using deep learning in neural networks
Yair Rivenson, Yibo Zhang, Harun Gunaydin +2
Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography. Here we demonstrate that a neural network can learn to perform phase…