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Holography

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Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.

ACS nano
We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the human ocular microbiome and resides on the cornea and conjunctiva. Using S. aureus-specific antibodies a...

Machine learning-based in-line holographic sensing of unstained malaria-infected red blood cells.

Journal of biophotonics
Accurate and immediate diagnosis of malaria is important for medication of the infectious disease. Conventional methods for diagnosing malaria are time consuming and rely on the skill of experts. Therefore, an automatic and simple diagnostic modality...

Deep transfer learning-based hologram classification for molecular diagnostics.

Scientific reports
Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microcopy. However, extensive computation is required to reconstruct object images fr...

Deep learning-based super-resolution in coherent imaging systems.

Scientific reports
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 enhance the resolution of both pixel size-limited and diffraction-lim...

Partially spatially coherent digital holographic microscopy and machine learning for quantitative analysis of human spermatozoa under oxidative stress condition.

Scientific reports
Semen quality assessed by sperm count and sperm cell characteristics such as morphology and motility, is considered to be the main determinant of men's reproductive health. Therefore, sperm cell selection is vital in assisted reproductive technology ...

Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Robust and reproducible profiling of cell lines is essential for phenotypic screening assays. The goals of this study were to determine robust and reproducible optical phase signatures of cell lines for classification with machine learning and to cor...

Label-free optical hemogram of granulocytes enhanced by artificial neural networks.

Optics express
An outstanding challenge for immunology is the classification of immune cells in a label-free fashion with high speed. For this purpose, optical techniques such as Raman spectroscopy or digital holographic microscopy have been used successfully to id...

Pixel super-resolution for lens-free holographic microscopy using deep learning neural networks.

Optics express
Lens-free holographic microscopy (LFHM) provides a cost-effective tool for large field-of-view imaging in various biomedical applications. However, due to the unit optical magnification, its spatial resolution is limited by the pixel size of the imag...

Translational and rotational manipulation of filamentous cells using optically driven microrobots.

Optics express
Optical cell manipulation has become increasingly valuable in cell-based assays. In this paper, we demonstrate the translational and rotational manipulation of filamentous cells using multiple cooperative microrobots automatically driven by holograph...

Deep learning-based color holographic microscopy.

Journal of biophotonics
We report a framework based on a generative adversarial network that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths. The trained network...