35 citations · 35 across the 1 of their papers we have counts for
19 papers
Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning
Yi Luo, Hyou-Arm Joung, Sarah Esparza +3
Particle agglutination assays are widely adapted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic particles are mixed with a test sa…
Dynamic imaging and characterization of volatile aerosols in e-cigarette emissions using deep learning-based holographic microscopy
Yi Luo, Yichen Wu, Liqiao Li +4
Various volatile aerosols have been associated with adverse health effects; however, characterization of these aerosols is challenging due to their dynamic nature. Here we present…
Neural network-based image reconstruction in swept-source optical coherence tomography using undersampled spectral data
Yijie Zhang, Tairan Liu, Manmohan Singh +4
Optical Coherence Tomography (OCT) is a widely used non-invasive biomedical imaging modality that can rapidly provide volumetric images of samples. Here, we present a deep learning…
Holographic image reconstruction with phase recovery and autofocusing using recurrent neural networks
Luzhe Huang, Tairan Liu, Xilin Yang +3
Digital holography is one of the most widely used label-free microscopy techniques in biomedical imaging. Recovery of the missing phase information of a hologram is an important st…
Deep learning-based virtual refocusing of images using an engineered point-spread function
Xilin Yang, Luzhe Huang, Yilin Luo +4
We present a virtual image refocusing method over an extended depth of field (DOF) enabled by cascaded neural networks and a double-helix point-spread function (DH-PSF). This netwo…
Recurrent neural network-based volumetric fluorescence microscopy
Luzhe Huang, Yilin Luo, Yair Rivenson +1
Volumetric imaging of samples using fluorescence microscopy plays an important role in various fields including physical, medical and life sciences. Here we report a deep learning-…