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    DEVICES, SYSTEMS, AND METHODS FOR VIRTUAL STAINING
    5.
    发明公开
    DEVICES, SYSTEMS, AND METHODS FOR VIRTUAL STAINING 审中-公开

    公开(公告)号：EP4321889A2

    公开(公告)日：2024-02-14

    申请号：EP23201486.0

    申请日：2013-03-15

    申请人： Genetic Innovations Inc.

    发明人： ROSENBLATT, Kevin, P. ,  YU, Jeffrey, N. ,  BRYANT-GREENWOOD, Peter

    IPC分类号： G01R33/483

    摘要： The disclosure herein provides methods, systems, and devices for virtually staining biological tissue for enhanced visualization without use of an actual dye or tag by detecting how each pixel of an unstained tissue image changes in waveform after staining with a certain dye(s) and/or tag(s) or other transformation under a certain electromagnetic radiation source, developing a virtual staining transform based on such detection, and applying such virtual staining transform to an unstained biological tissue to virtually stain the tissue.

    DIRECT INFERENCE BASED ON UNDERSAMPLED MRI DATA OF INDUSTRIAL SAMPLES
    9.
    发明公开
    DIRECT INFERENCE BASED ON UNDERSAMPLED MRI DATA OF INDUSTRIAL SAMPLES 审中-公开

    公开(公告)号：EP4202427A1

    公开(公告)日：2023-06-28

    申请号：EP21217638.2

    申请日：2021-12-23

    申请人： Orbem GmbH

    发明人： Coello Uribe, Jorge Eduardo ,  Kudielka, Guido ,  Gómez Damián, Pedro Agustín ,  Laparidou, Maria ,  Molina Romero, Miguel

    IPC分类号： G01N24/08 ,  G01R33/56 ,  G01R33/561 ,  G06T7/00 ,  B07C5/344 ,  G01N33/08 ,  G01R33/483

    摘要： Method for automated non-invasive identification of a predetermined feature in a multitude of industrial samples (102) of a predefined sample type, the method comprising the steps of: a) conveying an industrial sample (102) of the predefined sample type into an MRI scanner (106), b) recording in an MRI measurement for at least one slice or at least a partial volume of the industrial sample undersampled MRI data (300), comprising: - undersampled raw MRI data, comprising a multitude of time dependent signals for different phases, and/or - processed MRI data, obtained from processing undersampled raw MRI data, and c) analysing the undersampled MRI data (300) with an inference module (200) for identifying a predetermined feature of the industrial sample (102) using a machine learning module (204) that is trained for identifying the predetermined feature in industrial samples (102) of the predefined sample type from undersampled MRI data (300), wherein the inference module (200) comprises a memory (202) storing the machine learning module (204) and a processor (206) for controlling the inference module (200), wherein the inference module (200) is configured to provide the undersampled MRI data (300) as an input to the machine learning module (200) and to analyse the undersampled MRI data (300) using the machine learning module (204), wherein the machine learning module (204) is trained for identifying the predetermined feature in industrial samples (102) of the predefined sample type using a training set (302) comprising undersampled MRI data (300) of different training samples of the predefined sample type, wherein a fraction of the training samples comprises the predetermined feature and a fraction of the training samples does not comprise the predetermined feature.