The disclosure features systems and methods for measuring and diagnosing target constituents bound to labeling particles in a sample. The systems include a radiation source, a sample holder, a detector configured to obtain one or more diffraction patterns of the sample each including information corresponding to optical properties of sample constituents, and an electronic processor configured to, for each of the one or more diffraction patterns: (a) analyze the diffraction pattern to obtain amplitude information and phase information corresponding to the sample constituents; (b) identify one or more particle-bound target sample constituents based on at least one of the amplitude information and the phase information; and (c) determine an amount of at least one of the particle-bound target sample constituents in the sample based on at least one of the amplitude information and the phase information.

A method and system for performing incoherent color holographic microscopy imaging using light of various wavelengths, including modulating radiation at each wavelength to form two beams and detecting their intensity at a detector. The two beams include phase information that is retrieved from the phase shifted intensity recorded at the detector and holographic information is determined from the detected modulation of the two beams for each color. A processor is configured to receive the holographic information via a signal generated by the detector and the processor further generates a three-dimensional image of a target.

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. In some embodiments, the trained deep neural network simultaneously achieves phase-recovery and auto-focusing significantly extending the DOF of holographic image reconstruction.

An imaging flow cytometer device includes a housing holding a multi-color illumination source configured for pulsed or continuous wave operation. A microfluidic channel is disposed in the housing and is fluidically coupled to a source of fluid containing objects that flow through the microfluidic channel. A color image sensor is disposed adjacent to the microfluidic channel and receives light from the illumination source that passes through the microfluidic channel. The image sensor captures image frames containing raw hologram images of the moving objects passing through the microfluidic channel. The image frames are subject to image processing to reconstruct phase and/or intensity images of the moving objects for each color. The reconstructed phase and/or intensity images are then input to a trained deep neural network that outputs a phase recovered image of the moving objects. The trained deep neural network may also be trained to classify object types.

A holographic imaging device is disclosed. In one aspect, the holographic imaging device comprises an imaging unit comprising at least two light sources, wherein the imaging unit is configured to illuminate an object by emitting at least two light beams with the at least two light sources. A first and second light beams have different wave-vectors and wavelengths. The holographic imaging device further comprises a processing unit configured to obtain at least two holograms of the object by controlling the imaging unit to sequentially illuminate the object with respectively the first light beam and the second light beam, construct at least two 2D image slices based on the at least two holograms, wherein each 2D image slice is constructed at a determined depth within the object volume, and generate a three-dimensional image of the object based on a combination of the 2D image slices.

An interference imaging device includes a light interference generator that includes: a light wave splitter configured to reflect a part of incident light and to allow a remaining part of the incident light to pass through; a phase modulator configured to modulate a phase of incident light that has passed through the light wave splitter; and a reflector configured to reflect the phase-modulated incident light from the phase modulator so that the reflected, phase-modulated incident light overlaps with incident light that has been reflected by the light wave splitter.

A cell area extraction unit (241) extracts a cell area in a phase image that is created based on a hologram obtained by in-line holographic microscope (IHM). A background value acquisition unit (242) obtains a background value from phase values at a plurality of positions outside the cell area. An intracellular phase value acquisition unit (243) averages a plurality of phase values on a sampling line set at a position close to the periphery of a cell, while avoiding a central portion in which the phase value may be lowered in the cell area, to obtain an intracellular phase value. A phase change amount calculation unit (244) obtains the difference between the intracellular phase value and the background value. A phase change amount determination unit (245) compares the value of the difference with thresholds in two levels to determine whether the cell is in an undifferentiated state or an undifferentiation deviant state. It is thereby possible to automatically make a correct determination while removing the influence of a theoretical measurement error by IHM.

An optical method of characterizing an object comprises providing an object to be characterized, the object having at least one nanoscale feature; illuminating the object with coherent plane wave optical radiation having a wavelength larger than the nanoscale feature; capturing a diffraction intensity pattern of the radiation which is scattered by the object; supplying the diffraction intensity pattern to a neural network trained with a training set of diffraction intensity patterns corresponding to other objects with a same nanoscale feature as the object to be characterized, the neural network configured to recover information about the object from the diffraction intensity pattern; and making a characterization of the object based on the recovered information.

A holographic microscope configured to observe a sample is provided. The holographic microscope includes a light source, a light splitting element, a polarizing element, a phase modulation element, a light combining element, and a photosensitive element. The light source is configured to provide an illumination beam. The illuminating beam is transmitted through the light splitting element to form a first light beam and a second light beam, and the sample is disposed on a transmission path of the first light beam. The polarizing element and the phase modulation element are disposed on the transmission path of the first light beam or the second light beam. The first light beam and the second light beam are transmitted to the light combining element to form an interference beam. The photosensitive element is disposed on a transmission path of the interference beam to receive the interference beam to generate an optical signal.

Provided are an imaging system and an imaging device capable of generating a super-resolution interference fringe image of an object to be observed flowing through a flow channel. A light source that irradiates light in a first direction and irradiates light toward a flow channel through which an object to be observed flows in a second direction orthogonal to the first direction, an imaging sensor that has an imaging surface orthogonal to the first direction and on which a plurality of pixels are two-dimensionally arranged in a manner non-parallel to the second direction and that images light passing through the flow channel to output an interference fringe image, and an information processing device that generates a super-resolution interference fringe image based on a plurality of interference fringe images output from the imaging sensor are included.