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    IMAGE ADAPTIVE PHYSIOLOGICALLY PLAUSIBLE COLOR SEPARATION
    1.
    发明授权
    IMAGE ADAPTIVE PHYSIOLOGICALLY PLAUSIBLE COLOR SEPARATION 有权

    公开(公告)号：EP3005293B1

    公开(公告)日：2018-10-03

    申请号：EP14730102.2

    申请日：2014-05-28

    申请人： Ventana Medical Systems, Inc.

    发明人： BREDNO, Joerg ,  DIETZ, Lou ,  MARTIN, Jim F.

    IPC分类号： G06T7/11 ,  G06K9/00 ,  G06K9/46

    CPC分类号： G06K9/00127 ,  G06K9/4604 ,  G06T7/0014 ,  G06T7/11 ,  G06T2207/10024 ,  G06T2207/10064 ,  G06T2207/30024

    摘要： The subject disclosure presents systems and methods for separating colors in an image by automatically and adaptively adjusting reference vectors based on information specific to the assay being imaged, resulting in an optimized unmixing process that provides stain information that is physically and physiologically plausible. The reference vectors are optimized iteratively, based on minimizing non-negative color contributions, background contributions, high-frequencies in color channels specific to background or unwanted fluorescence, signals from known immunohistochemical markers, and pairs of stains known to carry physiologically independent information. Adjustments to the reference vectors may be allowed within a range that is predetermined based on measuring colors from multiple input images.

    AUTO-FOCUS METHODS AND SYSTEMS FOR DIGITAL IMAGING USING MUTLI-SPECTRAL TRAJECTORIES
    3.
    发明公开
    AUTO-FOCUS METHODS AND SYSTEMS FOR DIGITAL IMAGING USING MUTLI-SPECTRAL TRAJECTORIES 审中-公开

    公开(公告)号：EP3391116A1

    公开(公告)日：2018-10-24

    申请号：EP16823186.8

    申请日：2016-12-14

    申请人： Ventana Medical Systems, Inc.

    发明人： BREDNO, Joerg ,  MARTIN, Jim ,  SARKAR, Anindya

    IPC分类号： G02B7/38 ,  G02B21/36 ,  H04N1/387

    CPC分类号： G02B21/367 ,  G02B21/006 ,  H04N1/3876 ,  H04N5/23212

    摘要： A method and associated method and computer program product for acquiring focused images of a specimen on a slide, by determining optimal scanning trajectories. The method includes capturing a relatively low magnification image of the slide to locate the specimen, forming a grid that includes an arrangement of grid points, overlaying at least part of the grid over a field of view that covers at least part of the specimen, capturing a relatively high magnification Z-stack of images of the specimen within the field of view, determining a best focus for each grid point within said at least part of the grid to form a resulting grid of three dimensional points, and based on the resulting grid, determining one or more three dimensional scanning trajectories.

    ADAPTIVE CLASSIFICATION FOR WHOLE SLIDE TISSUE SEGMENTATION
    5.
    发明公开
    ADAPTIVE CLASSIFICATION FOR WHOLE SLIDE TISSUE SEGMENTATION 审中-公开
    自适应KLASSIFIZIERUNG VON GEWEBESEGMENTIERUNG MITVOLLSTÄNDIGENOBJEKTTRGERN

    公开(公告)号：EP3100205A1

    公开(公告)日：2016-12-07

    申请号：EP15703003.2

    申请日：2015-01-23

    申请人： Ventana Medical Systems, Inc.

    发明人： BREDNO, Joerg ,  CHUKKA, Srinivas ,  CHEN, Ting ,  CHEFD'HOTEL, Christophe ,  NGUYEN, Kien

    IPC分类号： G06K9/00 ,  G06K9/46 ,  G06K9/62 ,  G06K9/66

    CPC分类号： G06K9/00147 ,  G06K9/4642 ,  G06K9/4652 ,  G06K9/623 ,  G06K9/66 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/40 ,  G06T7/74 ,  G06T2207/20081 ,  G06T2207/30024

    摘要： A method of segmenting images of biological specimens using adaptive classification to segment a biological specimen into different types of tissue regions. The segmentation is performed by, first, extracting features from the neighborhood of a grid of points (GPs) sampled on the whole-slide (WS) image and classifying them into different tissue types. Secondly, an adaptive classification procedure is performed where some or all of the GPs in a WS image are classified using a pre-built training database, and classification confidence scores for the GPs are generated. The classified GPs with high confidence scores are utilized to generate an adaptive training database, which is then used to re-classify the low confidence GPs. The motivation of the method is that the strong variation of tissue appearance makes the classification problem more challenging, while good classification results are obtained when the training and test data origin from the same slide.

    摘要翻译： 使用自适应分类将生物样本的图像分割成不同类型的组织区域的方法。 通过以下步骤执行分割：首先，从全滑动（WS）图像上采样的点格网（GP）的邻域提取特征，并将其分类成不同的组织类型。 其次，使用预先构建的训练数据库对WS图像中的一些或全部GP进行分类，并且生成GP的分类置信度得分，进行自适应分类过程。 具有高置信度分数的分类GP用于生成适应性训练数据库，然后将其用于重新分类低置信度GP。 该方法的动机是，组织外观的强烈变化使得分类问题更具挑战性，而当训练和测试数据来自同一幻灯片时，可以获得良好的分类结果。

    SYSTEMS AND METHODS FOR COMPREHENSIVE MULTI-ASSAY TISSUE ANALYSIS
    6.
    发明公开
    SYSTEMS AND METHODS FOR COMPREHENSIVE MULTI-ASSAY TISSUE ANALYSIS 审中-公开
    系统和方法全方位多的分析组织分析

    公开(公告)号：EP3055835A1

    公开(公告)日：2016-08-17

    申请号：EP14781515.3

    申请日：2014-10-06

    申请人： Ventana Medical Systems, Inc.

    发明人： CHUKKA, Srinivas ,  SARKAR, Anindya ,  BREDNO, Joerg

    IPC分类号： G06T7/00

    摘要： The subject disclosure presents systems and methods for receiving a plurality of assay information along with a query for one or more features of interest, and projecting anatomical information from an anatomical assay onto a staining assay, for example an immunohistochemical (IHC) assay that is commonly registered with the anatomical assay, to locate or determine features appropriate for analysis. The anatomical information may be used to generate a mask that is projected on one or more commonly registered staining assays. A location of the feature of interest in the staining assay may be correlated with the anatomical context provided by the mask, with any features of interest that match the anatomical mask being selected or indicated as appropriate for analysis.

    AUTO-FOCUS METHODS AND SYSTEMS FOR MULTI-SPECTRAL IMAGING
    7.
    发明公开
    AUTO-FOCUS METHODS AND SYSTEMS FOR MULTI-SPECTRAL IMAGING 审中-公开
    AUTOFOKUSVERFAHREN UND SYSTEME ZUR MULTISPEKTRALEN BILDGEBUNG

    公开(公告)号：EP2989499A1

    公开(公告)日：2016-03-02

    申请号：EP14738847.4

    申请日：2014-07-15

    申请人： Ventana Medical Systems, Inc.

    发明人： BREDNO, Joerg ,  MARTIN, Jim, F. ,  SARKAR, Anindya

    IPC分类号： G02B21/24 ,  G02B21/36

    CPC分类号： G02B21/008 ,  G02B21/006 ,  G02B21/0072 ,  G02B21/16 ,  G02B21/244 ,  G02B21/367 ,  G06T7/80 ,  G06T2207/10056

    摘要： Techniques for acquiring focused images of a microscope slide are disclosed. During a calibration phase, a “base” focal plane is determined using non-synthetic and/or synthetic auto-focus techniques. Furthermore, offset planes are determined for color channels (or filter bands) and used to generate an auto-focus model. During subsequent scans, the auto-focus model can be used to quickly estimate the focal plane of interest for each color channel (or filter band) rather than re-employing the non-synthetic and/or synthetic auto-focus techniques.

    摘要翻译： 公开了用于获取显微镜幻灯片的聚焦图像的技术。 在校准阶段期间，使用非合成和/或合成自动对焦技术确定“基”焦平面。 此外，为色彩通道（或滤波器带）确定偏移平面，并用于生成自动对焦模型。 在随后的扫描期间，可以使用自动聚焦模型来快速估计每个颜色通道（或滤光片带）的感兴趣的焦平面，而不是重新采用非合成和/或合成的自动对焦技术。