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Disease detection algorithms trainable with small number of positive samples

机译:疾病检测算法占少量正样品

摘要

Disease detection from medical images is provided. In various embodiments, a medical image of a patient is read. The medical image is provided to a trained anatomy segmentation network. A feature map is received from the trained anatomy segmentation network. The feature map indicates the location of at least one feature within the medical image. The feature map is provided to a trained classification network. The trained classification network was pre-trained on a plurality of feature map outputs of the segmentation network. A disease detection is received from the trained classification network. The disease detection indicating the presence or absence of a predetermined disease.
机译:提供了来自医学图像的疾病检测。在各种实施例中,读取患者的医学图像。医学图像被提供给训练有素的解剖分割网络。从培训的解剖分段网络接收特征映射。特征映射表示医学图像中至少一个功能的位置。特征图提供给培训的分类网络。训练的分类网络在分割网络的多个特征映射输出上预先培训。从训练有素的分类网络接收疾病检测。疾病检测表明存在或不存在预定疾病。

著录项

  • 公开/公告号US10991100B2

    专利类型

  • 公开/公告日2021-04-27

    原文格式PDF

  • 申请/专利权人 INTERNATIONAL BUSINESS MACHINES CORPORATION;

    申请/专利号US202016738399

  • 发明设计人 MEHDI MORADI;CHUN LOK WONG;

    申请日2020-01-09

  • 分类号G06T7;G06K9;G16H50/20;G06N20;G06N3/04;G16H50/70;G06K9/62;G06N3/08;G16H30/40;G06N5;G06N20/10;G06N20/20;

  • 国家 US

  • 入库时间 2022-08-24 18:23:20

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