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    SYSTEMS AND METHODS FOR SAMPLE IMAGE CAPTURE USING INTEGRATED CONTROL
    1.
    发明申请
    SYSTEMS AND METHODS FOR SAMPLE IMAGE CAPTURE USING INTEGRATED CONTROL 审中-公开

    公开(公告)号：US20190170996A1

    公开(公告)日：2019-06-06

    申请号：US16175550

    申请日：2018-10-30

    Applicant: LIFE TECHNOLOGIES CORPORATION

    Inventor： Terence Tak-Shing TAM ,  Christopher MARTIN ,  Frank METTING ,  Jason MECHAM ,  Robert DAIN ,  Larry RYSTROM ,  Paul Adrian BOESCHOTEN ,  Steven W. LYTLE

    IPC: G02B21/36

    Abstract: Embodiments relate to systems and methods for sample image capture using integrated control. A digital microscope or other imaging device can be associated with a sample chamber containing cell, tissue, or other sample material. The chamber can be configured to operate using a variety of environmental variables, including gas concentration, temperature, humidity, and others. The imaging device can be configured to operate using a variety of imaging variables, including magnification, focal length, illumination, and others. A central system control module can be used to configure the settings of those hardware elements, as well as others, to set up and carry out an image capture event. The system control module can be operated to control the physical, optical, chemical, and/or other parameters of the overall imaging environment from one central control point. The variables used to produce the image capture can be configured to dynamically variable during the media capture event.

    SYSTEMS AND METHODS FOR AUTOFOCUS AND AUTOMATED CELL COUNT USING ARTIFICIAL INTELLIGENCE
    3.
    发明申请
    SYSTEMS AND METHODS FOR AUTOFOCUS AND AUTOMATED CELL COUNT USING ARTIFICIAL INTELLIGENCE 有权

    公开(公告)号：US20220120664A1

    公开(公告)日：2022-04-21

    申请号：US17501506

    申请日：2021-10-14

    Applicant: LIFE TECHNOLOGIES CORPORATION ,  CELLOMICS, INC.

    Inventor： Nicolas ROGNIN ,  Larry RYSTROM ,  Ognjen GOLUB ,  Jonathan PAULLIN ,  Nicholas DILIANI ,  Kim IPPOLITO

    IPC: G01N15/14 ,  G06V20/69 ,  G06T3/40 ,  G06N3/08 ,  G06N3/04

    Abstract: Systems and methods for autofocus using artificial intelligence include (i) capturing a plurality of monochrome images over a nominal focus range, (ii) identifying one or more connected components within each monochrome image, (iii) sorting the identified connected components based on a number of pixels associated with each connected component, (iv) generating a focus quality estimate of at least a portion of the sorted connected components using a machine learning module, and (iv) calculating a target focus position based on the focus quality estimate of the evaluated connected components. The calculated target focus position can be used to perform cell counting using artificial intelligence, such as by (i) generating a seed likelihood image and a whole cell likelihood image based on output—a convolutional neural network and (ii) generating a mask indicative quantity and/or pixel locations of objects based on the seed likelihood image.

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