Quality control of automated whole-slide analyses

    公开(公告)号:US11328420B2

    公开(公告)日:2022-05-10

    申请号:US16746101

    申请日:2020-01-17

    Abstract: The subject disclosure presents systems and methods for automatically selecting meaningful regions on a whole-slide image and performing quality control on the resulting collection of FOVs. Density maps may be generated quantifying the local density of detection results. The heat maps as well as combinations of maps (such as a local sum, ratio, etc.) may be provided as input into an automated FOV selection operation. The selection operation may select regions of each heat map that represent extreme and average representative regions, based on one or more rules. One or more rules may be defined in order to generate the list of candidate FOVs. The rules may generally be formulated such that FOVs chosen for quality control are the ones that require the most scrutiny and will benefit the most from an assessment by an expert observer.

    Methods and systems for evaluation of immune cell infiltrate in tumor samples

    公开(公告)号:US11250566B2

    公开(公告)日:2022-02-15

    申请号:US16752494

    申请日:2020-01-24

    Abstract: Immune context scores are calculated for tumor tissue samples using continuous scoring functions. Feature metrics for at least one immune cell marker are calculated for a region or regions of interest, the feature metrics including at least a quantitative measure of human CD3 or total lymphocyte counts. A continuous scoring function is then applied to a feature vector including the feature metric and at least one additional metric related to an immunological biomarker, the output of which is an immune context score. The immune context score may then be plotted as a function of a diagnostic or treatment metric, such as a prognostic metric (e.g. overall survival, disease-specific survival, progression-free survival) or a predictive metric (e.g. likelihood of response to a particular treatment course). The immune context score may then be incorporated into diagnostic and/or treatment decisions.

    Quality control of automated whole-slide analyses

    公开(公告)号:US10573001B2

    公开(公告)日:2020-02-25

    申请号:US15659654

    申请日:2017-07-26

    Abstract: The subject disclosure presents systems and methods for automatically selecting meaningful regions on a whole-slide image and performing quality control on the resulting collection of FOVs. Density maps may be generated quantifying the local density of detection results. The heat maps as well as combinations of maps (such as a local sum, ratio, etc.) may be provided as input into an automated FOV selection operation. The selection operation may select regions of each heat map that represent extreme and average representative regions, based on one or more rules. One or more rules may be defined in order to generate the list of candidate FOVs. The rules may generally be formulated such that FOVs chosen for quality control are the ones that require the most scrutiny and will benefit the most from an assessment by an expert observer.

    Adaptive classification for whole slide tissue segmentation

    公开(公告)号:US10102418B2

    公开(公告)日:2018-10-16

    申请号:US15222889

    申请日:2016-07-28

    Abstract: 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.

    Auto-Focus Methods and Systems for Multi-Spectral Imaging
    58.
    发明申请
    Auto-Focus Methods and Systems for Multi-Spectral Imaging 审中-公开
    自动对焦方法和多光谱成像系统

    公开(公告)号:US20160370565A1

    公开(公告)日:2016-12-22

    申请号:US14901700

    申请日:2014-07-15

    Abstract: 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.

    Abstract translation: 公开了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,为颜色通道(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,自动对焦模型可以用于快速估计每个颜色通道(或滤光片带)的感兴趣焦平面,而不是重新采用非合成和/或合成的自动对焦技术。

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