Disclosed are systems, devices and methods for imaging and image-based sorting of particles in a flow system, including cells in a flow cytometer. In some aspects, a system includes a particle flow device to flow particles through a channel, an imaging system to obtain image data of a particle during flow through the channel, a processing unit to determine a property associated with the particle and to produce a control command for sorting the particle based on sorting criteria associated with particle properties, and an actuator to direct the particle into one of a plurality of output paths of the particle flow device in real-time.

Systems and methods of assessing a probability that an individual will develop sepsis are provided. The systems and methods can include obtaining a set of parameters associated with the individual including white blood cell count (WBC) and monocyte distribution width (MDW) value, and determining whether the set of parameters provides an elevated risk status by comparing at least the WBC and the MDW value with respective predetermined criteria. In the event that the set of parameters is determined to provide the elevated risk status, the systems and methods can further include obtaining a secondary parameter associated with the individual; and providing the probability that the individual will develop sepsis.

Embodiments disclose a device for testing biological specimen. The device includes a sample carrier and a detachable cover. The sample carrier includes a specimen holding area. The detachable cover is placed on top of the specimen holding area. The detachable cover includes a magnifying component configured to align with the specimen holding area. The focal length of the magnifying component is from 0.1 mm to 8.5 mm. The magnifying component has a linear magnification ratio of at least 1.

In order to secure measurement reproducibility and a measurement accuracy by making it possible to automatically execute a bubble removal sequence as needed, the particle size distribution measurement device comprises a circulation flow channel through which the dispersion medium circulates, a flow cell arranged in the circulation flow channel, an imaging device that takes a particle image as being an image of a particle in the flow cell, and a bubble removal execution part that obtains bubble information which is obtained based on the particle image and which is about a bubble in the dispersion medium and that executes a bubble removal sequence to remove the bubble from the dispersion medium circulating in the circulation flow channel in case that the bubble information meets a predetermined condition.

An optical fiber forward scatter channel in a flow cytometer is disclosed. A detector system in the flow cytometer includes fiber optic cable for receiving scattered light from an incident laser light that is directed at cells/particles passing through the flow cytometer. The fiber optic cable delivers the scattered light to a sensor system, which collects data to perform analyses on the scattered light. Such analyses may include, for example, calculating the size of a cell/particle, counting cells/particles, and so on. The fiber optic cable is an inherently efficient and accurate filter for the acceptance or rejection of the scattered light.

A fluid delivery method for delivering a liquid sample to a flow cell including a taper section including a first and a second inner walls opposing the first inner wall, which is inclined to the second inner wall so that a distance between the first and the second inner walls at a downstream side of the taper section is shorter than a distance at an upstream side of the taper section, and including measurement flow path provided downstream of the taper section, through which a liquid sample flows together with a sheath fluid. The fluid delivery method includes sample introduction of delivering the liquid sample into the taper section along the second inner wall until the liquid sample reaches the measurement flow path, and sample pressing by delivering the sheath fluid into the taper section along the first inner wall after the liquid sample reaches the measurement flow path.

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.

Techniques for processing ore include the steps of causing an imaging capture system to record a plurality of images of a stream of ore fragments en route from a first location in an ore processing facility to a second location in the ore processing facility; correlating the plurality of images of the stream of ore fragments with at least one or more characteristics of the ore fragments using a machine learning model that includes a plurality of ore parameter measurements associated with the one or more characteristics of the ore fragments; determining, based on the correlation, at least one of the one or more characteristics of the ore fragments; and generating, for display on a user computing device, data indicating the one or more characteristics of the ore fragments or data indicating an action or decision based on the one or more characteristics of the ore fragments.

A device (1) is described and represented for the determination of the particle size and/or the particle shape and/or optical properties, such as transparency, of particles (2) in a particle stream (3), with a feeding device (4) for the feeding of the particles (2) to a measuring zone (5), wherein the particles (2) flow through the measuring zone (5), with at least one illuminating device (6) for illuminating the measuring zone (5), with at least two camera devices (7, 8), each of which photographs a measurement region (9, 10) of the measuring zone (5) associated with the corresponding camera device (7, 8), wherein a first camera device (7) photographs a first, preferably larger, measurement region (10) with a first, preferably lesser, magnification and a second camera device (8) photographs a second, preferably smaller, measurement region (9) with a second, preferably stronger, magnification, with an imaging optics (11) for imaging the measurement regions (9, 10), and with an evaluating device for determining the particle size and/or the particle shape from the photographs of the measurement regions (9, 10), wherein the imaging optics (11) comprises at least one optical element (14), at which and/or by which the light radiation emanating from the measuring zone (5) is divided into at least two beam portions. According to the invention, it is provided that the illuminating device (6) is designed such that the first measurement region (10) and the second measurement region (9) are always illuminated together, wherein the first measurement region (10) is illuminated with the same intensity as the second measurement region (9).

A method, system and computer-readable medium for assessing a disease condition of a cancer of a subject, including: receiving a blood sample from the subject; isolating a plurality of circulating tumor cells (CTCs) from the blood sample; measuring at least one of cell or cell nucleus sizes of each of the plurality of CTCs; determining a measured CTC size distribution of the plurality of CTCs based on the measuring; comparing the measured CTC size distribution to a reference CTC size distribution using a computer; and assigning the disease condition of the cancer of the subject based on the comparing.