1.1k citations · 2.1k across the 8 of their papers we have counts for
6 papers · 1 filter
Automated screening of sickle cells using a smartphone-based microscope and deep learning
Kevin de Haan, Hatice Ceylan Koydemir, Yair Rivenson +8
Sickle cell disease (SCD) is a major public health priority throughout much of the world, affecting millions of people. In many regions, particularly those in resource-limited sett…
Design of Task-Specific Optical Systems Using Broadband Diffractive Neural Networks
Yi Luo, Deniz Mengu, Nezih T. Yardimci +4
We report a broadband diffractive optical neural network design that simultaneously processes a continuum of wavelengths generated by a temporally-incoherent broadband source to al…
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…
Class-specific Differential Detection in Diffractive Optical Neural Networks Improves Inference Accuracy
Jingxi Li, Deniz Mengu, Yi Luo +2
Diffractive deep neural networks have been introduced earlier as an optical machine learning framework that uses task-specific diffractive surfaces designed by deep learning to all…
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…