Abstract: An all-optical Diffractive Deep Neural Network (D2NN) architecture learns to implement various functions or tasks after deep learning-based design of the passive diffractive or reflective substrate layers that work collectively to perform the desired function or task. This architecture was successfully confirmed experimentally by creating 3D-printed D2NNs that learned to implement handwritten classifications and lens function at the terahertz spectrum. This all-optical deep learning framework can perform, at the speed of light, various complex functions and tasks that computer-based neural networks can implement, and will find applications in all-optical image analysis, feature detection and object classification, also enabling new camera designs and optical components that can learn to perform unique tasks using D2NNs. In alternative embodiments, the all-optical D2NN is used as a front-end in conjunction with a trained, digital neural network back-end.

Abstract: A deep learning-based digital staining method and system are disclosed that enables the creation of digitally/virtually-stained microscopic images from label or stain-free samples based on autofluorescence images acquired using a fluorescent microscope. The system and method have particular applicability for the creation of digitally/virtually-stained whole slide images (WSIs) of unlabeled/unstained tissue samples that are analyzes by a histopathologist. The methods bypass the standard histochemical staining process, saving time and cost. This method is based on deep learning, and uses, in one embodiment, a convolutional neural network trained using a generative adversarial network model to transform fluorescence images of an unlabeled sample into an image that is equivalent to the brightfield image of the chemically stained-version of the same sample.

Abstract: A method for lens-free imaging of a sample or objects within the sample uses multi-height iterative phase retrieval and rotational field transformations to perform wide FOV imaging of pathology samples with clinically comparable image quality to a benchtop lens-based microscope. The solution of the transport-of-intensity (TIE) equation is used as an initial guess in the phase recovery process to speed the image recovery process. The holographically reconstructed image can be digitally focused at any depth within the object FOV (after image capture) without the need for any focus adjustment, and is also digitally corrected for artifacts arising from uncontrolled tilting and height variations between the sample and sensor planes. In an alternative embodiment, a synthetic aperture approach is used with multi-angle iterative phase retrieval to perform wide FOV imaging of pathology samples and increase the effective numerical aperture of the image.

Abstract: A portable colorimetric assay system includes an opto-mechanical reader configured to be detachably mounted to a mobile phone having a camera or other camera-containing portable electronic device. The opto-mechanical reader includes one or more light sources configured to illuminate a test sample holder and control sample holder disposed in the opto-mechanical reader along an optical path aligned with a camera of the mobile phone or other camera-containing portable electronic device. One or more serum separation membranes are disposed in the opto-mechanical reader and define a sample receiving pad configured to receive a blood sample. A moveable serum collection membrane is membrane is also disposed in the reader and is configured to contact the sample receiving pad in a first position and moveable to a second position where the serum collection membrane is disposed inside the test sample holder.

Abstract: A method of generating a color image of a sample includes obtaining a plurality of low resolution holographic images of the sample using a color image sensor, the sample illuminated simultaneously by light from three or more distinct colors, wherein the illuminated sample casts sample holograms on the image sensor and wherein the plurality of low resolution holographic images are obtained by relative x, y, and z directional shifts between sample holograms and the image sensor. Pixel super-resolved holograms of the sample are generated at each of the three or more distinct colors. De-multiplexed holograms are generated from the pixel super-resolved holograms. Phase information is retrieved from the de-multiplexed holograms using a phase retrieval algorithm to obtain complex holograms. The complex hologram for the three or more distinct colors is digitally combined and back-propagated to a sample plane to generate the color image.

Abstract: Methods and systems for generating a high-color-fidelity and high-resolution color image of a sample are disclosed; which fuses or merges a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform based colorization method. A holographic microscope is used to obtain holographic images which are used to computationally reconstruct a high-resolution mono-color holographic image of the sample. A lens-based microscope is used to obtain low resolution color images. A discrete wavelet transform (DWT) is used to generate a final image that merges the low-resolution components from the lens-based color image and the high-resolution components from the high-resolution mono-color holographic image.

Abstract: A label-free bio-aerosol sensing platform and method uses a field-portable and cost-effective device based on holographic microscopy and deep-learning, which screens bio-aerosols at a high throughput level. Two different deep neural networks are utilized to rapidly reconstruct the amplitude and phase images of the captured bio-aerosols, and to output particle information for each bio-aerosol that is imaged. This includes, a classification of the type or species of the particle, particle size, particle shape, particle thickness, or spatial feature(s) of the particle. The platform was validated using the label-free sensing of common bio-aerosol types, e.g., Bermuda grass pollen, oak tree pollen, ragweed pollen, Aspergillus spore, and Alternaria spore and achieved >94% classification accuracy. The label-free bio-aerosol platform, with its mobility and cost-effectiveness, will find several applications in indoor and outdoor air quality monitoring.

Abstract: A method of generating a color image of a sample includes obtaining a plurality of low resolution holographic images of the sample using a color image sensor, the sample illuminated simultaneously by light from three or more distinct colors, wherein the illuminated sample casts sample holograms on the image sensor and wherein the plurality of low resolution holographic images are obtained by relative x, y, and z directional shifts between sample holograms and the image sensor. Pixel super-resolved holograms of the sample are generated at each of the three or more distinct colors. De-multiplexed holograms are generated from the pixel super-resolved holograms. Phase information is retrieved from the de-multiplexed holograms using a phase retrieval algorithm to obtain complex holograms. The complex hologram for the three or more distinct colors is digitally combined and back-propagated to a sample plane to generate the color image.

Abstract: Methods and systems for generating a high-color-fidelity and high-resolution color image of a sample are disclosed; which fuses or merges a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform based colorization method. A holographic microscope is used to obtain holographic images which are used to computationally reconstruct a high-resolution mono-color holographic image of the sample. A lens-based microscope is used to obtain low resolution color images. A discrete wavelet transform (DWT) is used to generate a final image that merges the low-resolution components from the lens-based color image and the high-resolution components from the high-resolution mono-color holographic image.

Abstract: A portable rapid diagnostic test reader system includes a mobile phone having a camera and one or more processors contained within the mobile phone and a modular housing configured to mount to the mobile phone. The modular housing including a receptacle configured to receive a sample tray holding a rapid diagnostic test. At least one illumination source is disposed in the modular housing and located on one side of the rapid diagnostic test. An optical demagnifier is disposed in the modular housing interposed between the rapid diagnostic test and the mobile phone camera.

Abstract: A lens-free microscope for monitoring air quality includes a housing that contains a vacuum pump configured to draw air into an impaction nozzle. The impaction nozzle has an output located adjacent to an optically transparent substrate for collecting particles. One or more illumination sources are disposed in the housing and are configured to illuminate the collected particles on the optically transparent substrate. An image sensor is located adjacent to the optically transparent substrate, wherein the image sensor collects particle diffraction patterns or holographic images cast upon the image sensor. At least one processor is disposed in the housing and controls the vacuum pump and the one or more illumination sources. Image files are transferred to a separate computing device for image processing using machine learning to identify particles and perform data analysis to output particle images, particle size, particle density, and/or particle type data.

Abstract: A multi-well plate reader device includes an opto-mechanical attachment configured to attach/detach to a portable electronic device having a camera. The reader includes a plurality of excitation illumination sources and a slot that receives a well plate. Excitation and emission filters are incorporated into the housing. Optical fibers are located in the attachment and transmit fluorescent light emitted from the wells of the well plate through an optional lens and into the camera. The optical fibers have an input end adjacent to the wells and an output end formed in a header, wherein, in one embodiment, multiple optical fibers are positioned within a cross-sectional area projection defined by the wells and wherein the output ends of optical fibers are mounted in the header. The pattern of the optical fibers is mapped to individual wells in a calibration operation and stored in a fiber map.

Abstract: A microscopy method includes a trained deep neural network that is executed by software using one or more processors of a computing device, the trained deep neural network trained with a training set of images comprising co-registered pairs of high-resolution microscopy images or image patches of a sample and their corresponding low-resolution microscopy images or image patches of the same sample. A microscopy input image of a sample to be imaged is input to the trained deep neural network which rapidly outputs an output image of the sample, the output image having improved one or more of spatial resolution, depth-of-field, signal-to-noise ratio, and/or image contrast.

Abstract: A method of performing antimicrobial susceptibility testing (AST) on a sample uses a reader device that mounts on a mobile phone having a camera. A microtiter plate containing wells preloaded with the bacteria-containing sample, growth medium, and drugs of differing concentrations is loaded into the reader device. The wells are illuminated using an array of illumination sources contained in the reader device. Images of the wells are acquired with the camera of the mobile phone. In one embodiment, the images are transmitted to a separate computing device for processing to classify each well as turbid or not turbid and generating MIC values and a susceptibility characterization for each drug in the panel based on the turbidity classification of the array of wells. The MIC values and the susceptibility characterizations for each drug are transmitted or returned to the mobile phone for display thereon.

Abstract: A method of performing phase retrieval and holographic image reconstruction of an imaged sample includes obtaining a single hologram intensity image of the sample using an imaging device. The single hologram intensity image is back-propagated to generate a real input image and an imaginary input image of the sample with image processing software, wherein the real input image and the imaginary input image contain twin-image and/or interference-related artifacts. A trained deep neural network is provided that is executed by the image processing software using one or more processors and configured to receive the real input image and the imaginary input image of the sample and generate an output real image and an output imaginary image in which the twin-image and/or interference-related artifacts are substantially suppressed or eliminated.

Abstract: A method of generating a color image of a sample includes obtaining a plurality of low resolution holographic images of the sample using a color image sensor, the sample illuminated simultaneously by light from three or more distinct colors, wherein the illuminated sample casts sample holograms on the image sensor and wherein the plurality of low resolution holographic images are obtained by relative x, y, and z directional shifts between sample holograms and the image sensor. Pixel super-resolved holograms of the sample are generated at each of the three or more distinct colors. De-multiplexed holograms are generated from the pixel super-resolved holograms. Phase information is retrieved from the de-multiplexed holograms using a phase retrieval algorithm to obtain complex holograms. The complex hologram for the three or more distinct colors is digitally combined and back-propagated to a sample plane to generate the color image.

Abstract: The concentration of mercury in a sample is measured by a reader secured to a camera-containing mobile electronic device. The reader has holders for sample and control solutions. First and second light sources emitting light at different colors illuminate the sample and control holders. Each holder contains gold nanoparticles, thymine-rich aptamers, and sodium chloride. The light sources illuminate the sample and control holders. An image is captured of the transmitted light through the sample and control holders, wherein the image comprises two control regions of interest and two sample regions of interest. The device calculates the intensity of the two control regions of interest and the two sample regions of interest and generates intensity ratios for the sample and control, respectively, at each color. The device calculates a normalized color ratio based on the intensity ratios and outputs a concentration of mercury based on the normalized color ratio.

Abstract: A method of imaging a sample having birefringent crystals (or other materials) using a lens-free polarized microscopy device includes illuminating the sample contained on a sample holder with circularly polarized partially coherent or coherent light and capturing lower resolution holographic images of the birefringent crystals with an image sensor. A polarization analyzer unit made from a ?/4 retarder and a linear polarizer is positioned between the sample holder and the image sensor. The lower resolution holographic images are obtained with the polarization analyzer unit in two different orientations (e.g. ˜90° orientations). Phase-retrieved, higher resolution images of the birefringent crystals at the different orientations are obtained using the lower resolution holographic images. A differential image is generated from the respective phase-retrieved, higher resolution images. An object support mask is applied to identify the birefringent crystals which can then be pseudo-colored.

Abstract: A fluorescent dye and quencher mixture for reporting on nucleic acid amplification from a sample includes a fluorescent intercalating dye, a dye sequestering or quenching agent such as hydroxynapthol blue (HNB) or caffeine, and primers, dNTPs, and a nucleic acid polymerizing enzyme or fragment thereof. The presence of the dye in combination with the dye sequestering or quenching agent improves the overall dynamic range of the fluorescent signal as well as shortens the time needed for visualization or image capture of amplified nucleic acid. The fluorescent dye and quencher mixture also enables the detection of nucleic acids in samples having low copy numbers.

Abstract: A device and method for imaging fluorescently labeled molecules (e.g., nucleic acids) includes securing a modular attachment device to the mobile phone with a sample containing stretched, fluorescently labeled nucleic acid molecules and illuminating the sample with excitation light to cause the fluorescently labeled nucleic acid molecules to emit fluorescent light. Images of the nucleic acids are captured using a camera of the mobile phone. The images from the mobile phone are transferred to a remote computer for image processing and analysis. The images are processed by the remote computer to generate analysis data of sample, wherein the analysis data includes the length of nucleic acid molecules contained in the sample or the length of molecular sub-region(s). The mobile phone or another computing device receives from the remote computer the analysis data and displays at least some of the analysis data thereon.