TARGET CELL STATISTICAL METHOD, APPARATUS, AND SYSTEM

    公开(公告)号:US20250060357A1

    公开(公告)日:2025-02-20

    申请号:US18937747

    申请日:2024-11-05

    Abstract: A target cell statistical method, apparatus and system are provided. A cell image of a blood specimen is acquired by a cell image analysis apparatus. The blood specimen is derived from a blood sample to be tested. A number of target cells and a number of reference cells in the cell image are automatically identified by the cell image analysis apparatus. A number of reference cells in the blood sample to be tested is acquired by the cell image analysis apparatus, and a number of target cells in the blood sample to be tested is calculated by the cell image analysis apparatus, based on the number of target cells and the number of reference cells in the cell image and the number of reference cells in the blood sample to be tested.

    Modular Optical Analytic Systems and Methods

    公开(公告)号:US20250044234A1

    公开(公告)日:2025-02-06

    申请号:US18747083

    申请日:2024-06-18

    Applicant: ILLUMINA, INC.

    Abstract: A system includes a plurality of modular subassemblies and a plate; wherein each modular subassembly comprises an enclosure and a plurality of optical components aligned to the enclosure, and each enclosure comprises a plurality of mounting structures; and wherein each modular subassembly is mechanically coupled to the plate by attachment of a mounting structure of the modular subassembly directly to a corresponding mounting structure located on the plate, such that by mechanically coupling each modular subassembly to the plate using the mounting structure of the modular subassembly and the corresponding mounting structure on the plate, adjacent modular subassemblies are aligned to each other upon such attachment, and wherein two of the modular subassemblies mechanically coupled to the plate are also attached to each other by mechanically coupling an alignment structure on one of the two modular subassemblies to a respective alignment structure on the other of the two modular subassemblies.

    Device for medical analyses with impedance signal processing

    公开(公告)号:US12196662B2

    公开(公告)日:2025-01-14

    申请号:US17606101

    申请日:2020-04-24

    Abstract: A device for medical analyses with cellular impedance signal processing comprises a memory (4) arranged to receive pulse data sets, each pulse data set comprising impedance value data that are associated each time with a time marker, these data together representing a curve of cellular impedance values that are measured as a cell passes through a polarized opening, a computer (6) arranged to process a pulse data set by determining a rotation value indicating whether the cell from which this pulse data set has been taken has undergone a rotation during its passage through the polarized opening, and a classifier (8) arranged to retrieve from the computer (6) a given pulse data set, and to use the resulting rotation value to classify the given pulse data set in a rotation pulse data set group (10) or a rotationless pulse data set group (12).

    WIDEFIELD INTERFEROMETRIC DEFOCUS-ENHANCED (WIDE) MID-INFRARED (MIR) PHOTOTHERMAL MICROSCOPY

    公开(公告)号:US20250012695A1

    公开(公告)日:2025-01-09

    申请号:US18761564

    申请日:2024-07-02

    Abstract: A wide-field microscopy system and method for imaging a sample include directing infrared light onto the sample to selectively heat the sample. Probe light is also directed onto the sample. An objective collects the probe light after it interacts with the sample. The collected probe light is detected at a detector. A relative distance between the objective and sample is adjusted to introduce an optical defocus enhancement to enhance detection of a change in detected probe light that is indicative of infrared absorption by the sample.

    Systems and Methods of Cell Sorting Implementing Artificial Intelligence

    公开(公告)号:US20250003859A1

    公开(公告)日:2025-01-02

    申请号:US18756372

    申请日:2024-06-27

    Abstract: Disclosed herein are apparatuses, systems, as well as related methods, computing devices, and computer-readable media related to real time cell sorter cell sorting using embeddings. For example, in some embodiments a method may comprise receiving first cell sorter data. The first cell sorter data may include cell sorter data including microscopy data, hyperspectral imaging data, high-dimensional vector data, or one or more combinations thereof. In some embodiments, the cell sorter data may include quantitative fluorescence data expressed as one or more of antibodies bound per cell, antibody binding capacity (ABC), molecules of equivalent soluble fluorochrome (MESF), one or more other quantitative indicators of fluorescence, or one or more combinations thereof. In some embodiments, the quantitative fluorescence data includes one or more fluorescence signals from: one or more fluorescent proteins, one or more fluorescent dyes, one or more fluorescently conjugate antibodies, or one or more combinations thereof.

    METHOD AND APPARATUS FOR DETERMINING NANOPARTICLE PROPERTIES OF NANOPARTICLES IN A SAMPLE

    公开(公告)号:US20240418627A1

    公开(公告)日:2024-12-19

    申请号:US18708291

    申请日:2021-11-09

    Abstract: A method of determining nanoparticle properties of nanoparticles (2) included in a sample (1), comprising the steps of collecting sequential frames of images by employing an interferometric microscope device (110), wherein the sample (1) is illuminated with illumination light (3) from a coherent light source device (111) and the images are created by scattering light (4) from the nanoparticles (2) superimposed with non-scattered reference light, said scattering light and reference light having a wavelength larger than a cross-sectional dimension of the nanoparticles (2), tracking the nanoparticles (2) in the sequential frames of images, wherein at least one interferometric point spread function (iPSF) feature of each of the nanoparticles (2) is established and nanoparticle trajectory motion data are determined for each nanoparticle (2), comprising the nanoparticle positions in each frame, for each nanoparticle (2), calculating a nanoparticle size d from the trajectory motion data of the nanoparticle and calculating an interferometric nanoparticle contrast from the at least one iPSF feature of the nanoparticle.

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