A method for analyzing microorganisms arranged in a sample is provided, the sample including a viability marker to modify an optical property of the microorganisms in different ways depending on whether they are dead or alive, the method including illumination of the sample and acquisition of an image of the latter by an image sensor, the image sensor then being exposed to an exposure light wave; determining positions of different microorganisms from the acquired image; applying a propagation operator to calculate at least one characteristic value of the exposure light wave at each radial position and at a plurality of distances from the detection plane representing a change in the characteristic value between the image sensor and the sample; and identifying living microorganisms according to each profile.

A microscope system is provided with a microscope that acquires images at least at a first magnification and a second magnification higher than the first magnification, and a processor. The processor is configured to specify a type of a container in which a specimen is placed, and when starting observation of the specimen placed in the container at the second magnification, the processor is configured to specify an observation start position by performing object detection according to the type of container on a first image that includes the container acquired by the microscope at the first magnification, and control a relative position of the microscope with respect to the specimen such that the observation start position is contained in a field of view at the second magnification of the microscope.

Irradiation light in a visible light region is irradiated to a sample while switching irradiation of infrared light IR having a wavelength that corresponds to the infrared absorption spectrum of an observation target material included in the sample between a first state and a second state. A first image and a second image are generated based on the phase distribution, the intensity distribution, and the polarization direction distribution of the light including the irradiation light that has passed through the sample in synchronization with the switching of the infrared light IR irradiation between the first state and the second state. Subsequently, an output image is generated so as to represent one from among the position, size, and shape based on the difference and/or ratio with respect to the pixel values for each pixel between the first image and the second image.

A computational microscope and a method for its operation are disclosed. In some embodiments, the microscope maps points on a sample to point in an intensity pattern on a one-to-many basis. The microscope utilizes illumination angle coding, polarization coding, amplitude coding, and phase coding to capture more information than prior art computational microscopes. Although the resulting intensity patterns are not human-interpretable images of the sample, they contain more information about the sample, by virtue of the aforementioned coding techniques, than is captured by prior-art microscopes. Machine-learning algorithms, such as neural networks, are used to analyze the intensity patterns and extract useful information, such as cellular events or cell behavior.

A system and method for analyzing bodily fluid include a sample holder holding a bodily fluid sample, an image capture device generating an image of the bodily fluid sample comprising a plurality of fields of view. An image processor is programmed to determine a biofilm in the bodily fluid sample from the image, determine a biofilm area or volume within each of the plurality of fields of view to form a plurality of biofilm areas, determine a total biofilm area or total biofilm volume by adding the plurality of biofilm areas, determine a first value corresponding to a comparison of the total biofilm area or the total biofilm volume and a total volume of the bodily fluid sample, and classify the first value into a classification. An analyzer, using the classification, displays an indicator on a display for indicating the classification of the biofilm within the bodily fluid sample.

This document describes methods, systems and computer program products directed to imaging blood cells. The subject matter described in this document can be embodied in a method of classifying white blood cells (WBCs) in a biological sample on a substrate. The method includes acquiring, by an image acquisition device, a plurality of images of a first location on the substrate, and classifying, by a processor, objects in the plurality of images into WBC classification groups. The method also includes identifying, by a processor, objects from at least some classification groups, as unclassified objects, and displaying, on a user interface, the unclassified objects and at least some of the classified objects.

The invention provides a technology for promptly determining bacterial identification or an antimicrobial susceptibility testing. In the invention, first, a state where the bacteria are divided is monitored by performing microscopic observation with respect to the shape or the number of bacteria in each of wells of a culture plate for bacterial identification culture or the antimicrobial susceptibility testing. In addition, the shape, the number or the area of the bacteria are interpreted from the image obtained by the microscopic observation whether or not the bacteria proliferate at a stage from an induction phase to a logarithmic phase, and the time-dependent changes thereof are made into a graph. From the graph, it is determined whether or not the bacteria proliferate for each measurement, the determination results are displayed on the screen, and accordingly, the result of the antimicrobial susceptibility is provided every time when the measurement is performed (FIG. 12).

A light sheet fluorescence microscope includes a light source configured to emit excitation light suitable for inducing fluorescent light emitted from a specimen, a detector configured to detect the fluorescent light from the specimen, and an optical system configured to illuminate the specimen with a light sheet formed from the excitation light, and to guide the fluorescent light from the illuminated specimen to the detector. The optical system includes an objective facing the specimen, the objective being configured to collect the fluorescent light emitted from the specimen. The light source is further configured to emit manipulation light suitable for photomanipulating the specimen. The optical system is further configured to direct the manipulation light through a spatially limited sub-area of an entrance pupil of the objective onto the specimen along a light propagation direction which is different from a light propagation direction of the light sheet.

Methods and systems for generating non-diffracting light sheets for multicolor fluorescence microscopy are disclosed. A method for generating a non-diffracting light patterned Bessel sheet comprises transmitting an input light beam through a Fourier transform lens the input light beam has a spatial intensity pattern at a first plane, and a Fourier plane is formed after the Fourier transform lens to obtain a first light beam; transmitting the first light beam through an annulus mask to obtain a second light beam; and transmitting the second light beam through an excitation objective lens to form a non-diffracting patterned light sheet. A method for generating a non-diffracting light line Bessel sheet comprises transmitting an input light beam at a first lane through an annulus mask to obtain a first light beam; and transmitting the first light beam through an excitation objective lens to form a non-diffracting Bessel light sheet.

A sample observation device includes: an emission optical system that emits planar light to a sample on an XZ plane; a scanning unit that scans the sample in a Y-axis direction so as to pass through an emission surface of the planar light; an imaging optical system that has an observation axis inclined with respect to the emission surface and forms an image of observation light generated in the sample; an image acquisition unit that acquires a plurality of pieces of XZ image data corresponding to an optical image of the observation light; and an image generation unit 8 that generates XY image data based on the plurality of pieces of XZ image data. The image generation unit extracts an analysis region of the plurality of pieces of XZ image data acquired in the Y-axis direction, integrates brightness values of at least the analysis region in a Z-axis direction to generate X image data, and combines the X image data in the Y-axis direction to generate the XY image data.