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SYSTEMS AND METHODS FOR BRAIN HEMORRHAGE CLASSIFICATION IN MEDICAL IMAGES USING AN ARTIFICIAL INTELLIGENCE NETWORK

机译:使用人工智能网络在医学图像中脑出血分类的系统和方法

摘要

Systems and methods for rapid, accurate, fully-automated, brain hemorrhage deep learning (DL) based assessment tools are provided, to assist clinicians in the detection & characterization of hemorrhages or bleeds. Images may be acquired from a subject using an imaging source, and preprocessed to cleanup, reformat, and perform any needed interpolation prior to being analyzed by an artificial intelligence network, such as a convolutional neural network (CNN). The artificial intelligence network identifies and labels regions of interest in the image, such as identifying any hemorrhages or bleeds. An output for a user may also include a confidence value associated with the identification.
机译:提供了快速,准确,全自动化,脑出血深度学习(DL)评估工具的系统和方法,以帮助临床医生在出血或出血的检测和表征中。可以使用成像源从对象获取图像,并预处理以在由人工智能网络(例如卷积神经网络(CNN)分析之前进行清理,重新编辑和执行任何所需的插值。人工智能网络识别和标记图像的感兴趣区域,例如识别任何出血或出血。用于用户的输出还可以包括与识别相关联的置信值。

著录项

  • 公开/公告号US2021082566A1

    专利类型

  • 公开/公告日2021-03-18

    原文格式PDF

  • 申请/专利权人 THE GENERAL HOSPITAL CORPORATION;

    申请/专利号US201816644779

  • 发明设计人 SYNHO DO;MICHAEL LEV;GILBERTO GONZALEZ;

    申请日2018-09-07

  • 分类号G16H30/40;G06T7;G06T7/11;G06T5;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-24 17:46:23

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