Methods and apparatus are described herein for measurement of droplets dispensed from a printhead of an inkjet printer onto a substrate. An inkjet printer described herein comprises a printhead assembly comprising a printhead and an imaging system, the imaging system comprising a camera and a strobed LED source; and a deposition unit for positioning a substrate to receive droplets dispensed from the printhead and for imaging the droplets using the imaging system and the strobed LED source. Methods described herein comprise dispensing droplets of a liquid from a printhead of a printhead assembly of an inkjet printer onto a substrate; positioning the substrate with respect to an imaging system coupled to the printhead assembly, the imaging system comprising a camera and an LED light source; and imaging the droplets on the substrate by relatively scanning the substrate and the imaging system and strobing the LED light source.

Systems and methods for classifying T cells by activation state are disclosed. The system includes a cell analysis pathway, a time-resolved autofluorescence decay spectrometer, a processor, and a non-transitory computer-readable memory. The memory is accessible to the processor and has stored thereon instructions. The instructions, when executed by the processor, cause the processor to: a) receive the time-resolved autofluorescence decay signal; b) compute at least a first phasor coordinate at a first frequency and a second phasor coordinate at a second frequency from the time-resolved autofluorescence decay signal, wherein the first and second frequency are different; and c) compute an activation prediction for the T cell using at least the first phasor coordinate and the second phasor coordinate.

Various embodiments described herein relate to apparatuses and methods for detecting fluid particles and their characteristics. In various embodiments, a device for detecting fluid particles and their characteristics may comprise a lens free holographic microscope configured to collect fluid particles via inertial impaction. In various embodiments, the collection media may be replaceable within the apparatus. In various embodiments, the impactor nozzle may be selectively configured to avoid optical reflections and scattering from illumination light passing through the nozzle. Various embodiments are directed to a collection media assembly for receiving particles from a volume of fluid within a fluid composition sensor. A collection media assembly may comprise a collection media, an orifice, a seal engagement portion and a frame element configured to facilitate the serial use of a plurality of collection media assemblies within a fluid composition sensor.

In relation to application of artificial intelligence to image analysis of particles, to make it possible to provide data for machine learning corresponding to user demands while making it possible to reduce, as much as possible, man-hours taken to, for example, prepare vast amounts of actual image data obtained by actually capturing images of particles, the present invention generates virtual particle image data, which is image data of a virtual particle, on the basis of a predetermined condition, generates label data corresponding to the virtual particle, and associates the virtual particle image data with the label data.

A disposable injection moulded flow cell or cuvette for use in flow cytometer for in vitro assaying of human or animal whole blood and to an investigation method using the flow cytometer. The present disclosure provides a cuvette for use in an optical flow cytometer, comprising a cuboid sheath preparation area, a curved sample injection area with a rectangular cross section, a pyramidal shaped flow formation area, and a sample injector which is arranged in the transition area from the cuboid sheath preparation area to the curved sample injection area.

The invention relates to a method and system for characterizing particles using a flow cytometer comprising detecting radiated light from the particles using two or more detectors positioned to allow for the detection in two or more angular directions and generating a waveform, as a digital representation for the detected radiated light for each of said angulation direction. The waveforms are transformed using one or more basis functions to obtain one or more coefficients characterizing the waveform. The one or more coefficients characterizing the waveform preferably correspond to properties of the particle(s), thereby enabling analysis of physical properties of the particles (such as size, shape, refractive index) or biological properties of the particles (such as cell type, cell cycle state or localization or distribution of molecules within the cell and/or on the cell surface). In preferred embodiments the method and system are used for a label-free sorting of particles, in particular biological cells.

The types of cells that cannot be determined by use of a conventional scattergram are determined. The problem is solved by a cell analysis method for analyzing cells contained in a biological sample, by using a deep learning algorithm having a neural network structure, the cell analysis method including: causing the cells to flow in a flow path; obtaining a signal strength of a signal regarding each of the individual cells passing through the flow path, and inputting, into the deep learning algorithm, numerical data corresponding to the obtained signal strength regarding each of the individual cells; and on the basis of a result outputted from the deep learning algorithm, determining, for each cell, a type of the cell for which the signal strength has been obtained.

A system is disclosed that enables the automated measurement of cellular mechanical parameters at high throughputs. The microfluidic device uses intersecting flows to create an extensional flow region where the cells undergo controlled stretching. Cells are focused into streamlines prior to entering the extensional flow region. In the extensional region, each cell's deformation is measured with an imaging device. Automated image analysis extracts a range of independent biomechanical parameters from the images. These may include cell size, deformability, and circularity. The single cell data that is obtained may then be used to in a variety of ways. Scatter density plots of deformability and circularity may be developed and displayed for the user. Mechanical parameters such as deformability and circularity may be gated or thresholded to identify certain cells of interest or sub-populations of interest. Similarly, the mechanical data obtained using the device may be used as cell signatures.

Provided are a captured image evaluation apparatus, a captured image evaluation method, and a captured image evaluation program capable of evaluating a thickness and a density of stacked cultured cells in a short imaging time. The captured image evaluation apparatus includes: an image acquisition section 52 that acquires captured images obtained by imaging a subject under a condition in which a numerical aperture of an objective lens is changed; a thickness estimation section 53 that estimates a thickness of the subject on the basis of a low NA captured image obtained under a condition in which the numerical aperture of the objective lens is relatively small; and a density estimation section 54 that estimates a density of the subject on the basis of a high NA captured image obtained under a condition in which the numerical aperture of the objective lens is relatively large.

An analysis method and device including detecting at least one particle of matter in a fluid inside in a reaction chamber and correlating a change in the particle to a physicochemical property of the matter.