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Systems and methods for training a statistical model to predict tissue characteristics for a pathology image

机译:用于训练统计模型的系统和方法,以预测病理图像的组织特征

摘要

In some aspects, the described systems and methods provide for a method for training a statistical model to predict tissue characteristics for a pathology image. The method includes accessing annotated pathology images. Each of the images includes an annotation describing a tissue characteristic category for a portion of the image. A set of training patches and a corresponding set of annotations are defined using an annotated pathology image. Each of the training patches in the set includes values obtained from a respective subset of pixels in the annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels. The statistical model is trained based on the set of training patches and the corresponding set of patch annotations. The trained statistical model is stored on at least one storage device.
机译:在一些方面,所描述的系统和方法提供了一种训练统计模型以预测病理图像的组织特征的方法。 该方法包括访问注释的病理学图像。 每个图像包括描述用于图像的一部分的组织特征类别的注释。 使用带注释的病理图像定义了一组训练补丁和相应的注释集。 该组中的每个训练补丁包括从注释的病理图像中的相应像素子集获得的值,并且与基于与各个像素子集相关联的注释确定的相应补丁注释相关联。 统计模型是根据训练补丁集的培训和相应的贴片注释培训。 训练的统计模型存储在至少一个存储设备上。

著录项

  • 公开/公告号US11195279B1

    专利类型

  • 公开/公告日2021-12-07

    原文格式PDF

  • 申请/专利权人 PATHAI INC.;

    申请/专利号US202016841827

  • 发明设计人 ANDREW H. BECK;ADITYA KHOSLA;

    申请日2020-04-07

  • 分类号G06T7;G06T7/194;G06N5/04;G06F16/58;G16H50/50;G16H10/20;G06K9/62;G16H50/20;

  • 国家 US

  • 入库时间 2022-08-24 22:38:36

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