Some embodiments of the present disclosure relate to systems and methods including generating, by infrared spectroscopy, spectra data identifying quantities and associated wavelengths of radiation absorption for each of a plurality of wine samples as determined by the infrared spectroscopy; converting the spectra data for each wine sample to a set of discretized data; transforming the discretized data into a visual image representation of each respective wine sample, the visual image representation of each wine sample being an optically recognizable representation of the corresponding converted set of discretized data; and storing a record including the visual image representation of each wine sample in a memory.

Systems and methods here may be used for automated alignment and focus adjustment for one or multiple sample gemstones on a stage, including determining gemstone sample tilt based on image data, automatically moving a stage to align the tilted sample, determining a focal plane that overlaps a focal point of a camera with the gemstone, and automatically moving a stage to the focal plane.

A system includes a light source configured to emit a probing beam to illuminate an optical element, and a rotating structure to which the optical element is mounted. The system also includes a controller configured to control the rotating structure to rotate to change a tilt angle of the optical element with respect to a propagation direction of the probing beam. The system also includes an image sensor configured to receive one or more scattered beams output from the optical element illuminated by the probing beam, and generate a plurality of sets of speckle pattern image data when the optical element is arranged at a plurality of tilt angles within a predetermined tilting range. The controller is configured to process the plurality of sets of speckle pattern image data to determine respective weights of volumetric scattering and surface scattering in an overall scattering of the optical element.

A sputum image processing assembly for processing sputum in a sputum sample container, and method of processing an image of the sputum. The assembly includes a light source to illuminate the sputum, a light sensor to acquire a reflected light from the illuminated sputum, a light enclosure to limit a light between the light source and the light sensor, and an image processor module to generate an image of the sputum with the acquired light. Further disclosed is a method of processing a plurality of sputum samples over time. The method includes acquiring a first sputum image of a first sputum sample, analyzing the first sputum image to determine first color information, acquiring a second sputum image of a second sputum sample, analyzing the second sputum image to determine second color information, and creating a time-based sputum report based on the first color information and the second color information.

An observation apparatus includes a case having a transmissive window, an image sensor, an optical system, and a light source housed in the case, and an optical deflection unit. The optical system is configured to condense light incident inside the case to form an image of a sample inside a container. The light source is configured to emit light to the outside of the case without passing through the optical system. The optical deflection unit is configured to deflect light emitted to the outside of the case from the light source to a first direction proceeding toward the transmissive window. An angle of exit between the first direction and an optical axis of the optical system is different from an angle of incidence between a second direction in which light emitted to the outside of the case is incident on the optical deflection unit, and the optical axis.

The ability to obtain and digitise pathology samples (such as in histopathology or cytopathology) has opened up the possibility of accurate and automated computer operated analysis, or computer-assisted analysis, when diagnosing a wide range of medical conditions. A typical digital pathology image analysis pipeline involves a large number of image pre-processing and processing operations. Small changes in the parameters used in these algorithms might lead to significant changes in the eventual pathological finding. Accordingly, the present application proposes to perform a sensitivity analysis on a digital pathology image analysis pipeline to assess the sensitivity of a given pathology result to changes of parameters in the digital pathology image analysis pipeline.

A single unit, handheld field portable apparatus and method for analyzing Ochratoxin A (OTA) in rice quality monitoring, based on fluorescence signal output. Aliquots may be analyzed by adding at least one or more reagents to the sample aliquot that reacts selectively with an analyte contained therein. The reaction product, which is selective for the analyte of interest and proportional to its concentration, is measured with an appropriate detector. This enables simple and accurate testing of samples using time honored wet-chemical analysis method in microliter volume regimes while producing remarkably small volumes of waste. The device includes a multipurpose controller board for processing and analysis purpose, a camera which is integrated with the controller, a resistive touch liquid crystal display to view the results, a light emitting diode to emit the UV light, and a power bank. The device may operate using a touch display.

The present invention discloses a method and an apparatus for measuring leaf nitrogen content (LNC), and belongs to the spectral analysis and artificial intelligence (AI) field. The method includes the following steps: (1) obtaining a single-band image of a target leaf illuminated by a light source in a single feature band; (2) repeating step (1), to collect image information in four feature bands; (3) combining the collected images in the four feature bands into a four-channel spectral image; (4) training a deep learning model by using the spectral image and a corresponding nitrogen content label, to obtain a nitrogen content prediction model; (5) transplanting the trained nitrogen content prediction model into an AI control system; (6) collecting information about a to-be-predicted leaf sample, predicting nitrogen content by using an AI sensor equipped with the AI control system, and outputting the predicted nitrogen content.

A method for analyzing 2D material thin film and a system for analyzing 2D material thin film are disclosed. The detection method includes the following steps: capturing sample images of 2D material thin films; measuring the 2D material thin films by a Raman spectrometer; performing a visible light hyperspectral algorithm on the sample images by a processor to generate a plurality of visible light hyperspectral images; performing a training and validation procedure, performing an image feature algorithm on the visible light hyperspectral images, and establishing a thin film prediction model based on a validation; and capturing a thin-film image to be measured by the optical microscope, performing the visible light hyperspectral algorithm, and then generating a distribution result of the thin-film image to be measured according to an analysis of the thin film prediction model.

Provided are an analyzer that analyzes a specimen with high accuracy and an analysis method for analyzing a specimen with high accuracy. The analyzer according to the present disclosure include a first reaction vessel which contains a reagent, a second reaction vessel which contains a specimen and the reagent, a detector which detects optical characteristics of the first reaction vessel and optical characteristics of the second reaction vessel, and a controller which analyzes components of the specimen in the second reaction vessel using the optical characteristics of the first reaction vessel as a baseline.