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Holography

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Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...

Full-color retinal-projection near-eye display using a multiplexing-encoding holographic method.

Optics express
We propose a novel method to construct an optical see-through retinal-projection near-eye display using the Maxwellian view and a holographic method. To provide a dynamic full-color virtual image, a single phase-only spatial light modulator (SLM) was...

Towards real-time photorealistic 3D holography with deep neural networks.

Nature
The ability to present three-dimensional (3D) scenes with continuous depth sensation has a profound impact on virtual and augmented reality, human-computer interaction, education and training. Computer-generated holography (CGH) enables high-spatio-a...

High-throughput label-free cell detection and counting from diffraction patterns with deep fully convolutional neural networks.

Journal of biomedical optics
SIGNIFICANCE: Digital holographic microscopy (DHM) is a promising technique for the study of semitransparent biological specimen such as red blood cells (RBCs). It is important and meaningful to detect and count biological cells at the single cell le...

Digital holographic deep learning of red blood cells for field-portable, rapid COVID-19 screening.

Optics letters
Rapid screening of red blood cells for active infection of COVID-19 is presented using a compact and field-portable, 3D-printed shearing digital holographic microscope. Video holograms of thin blood smears are recorded, individual red blood cells are...

Single Cell Analysis of Stored Red Blood Cells Using Ultra-High Throughput Holographic Cytometry.

Cells
Holographic cytometry is introduced as an ultra-high throughput implementation of quantitative phase imaging of single cells flowing through parallel microfluidic channels. Here, the approach was applied for characterizing the morphology of individua...

Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning.

Lab on a chip
Particle agglutination assays are widely adopted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic particles are mixed with a test sample that potentially contains the target antigen, as a result of whic...

Pattern Recognition of Holographic Image Library Based on Deep Learning.

Journal of healthcare engineering
The final loss function in the deep learning neural network is composed of other functions in the network. Due to the existence of a large number of non-linear functions such as activation functions in the network, the entire deep learning model pres...

Speeding up reconstruction of 3D tomograms in holographic flow cytometry deep learning.

Lab on a chip
Tomographic flow cytometry by digital holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution in 3D. Although this modality allows us ...

Deep Learning-Based Phenotypic Assessment of Red Cell Storage Lesions for Safe Transfusions.

IEEE journal of biomedical and health informatics
This study presents a novel approach to automatically perform instant phenotypic assessment of red blood cell (RBC) storage lesion in phase images obtained by digital holographic microscopy. The proposed model combines a generative adversarial networ...