首页> 外国专利> DEEP NETWORK LUNG TEXTURE RECOGNITON METHOD COMBINED WITH MULTI-SCALE ATTENTION

DEEP NETWORK LUNG TEXTURE RECOGNITON METHOD COMBINED WITH MULTI-SCALE ATTENTION

机译:深度网络肺纹理认可方法结合多尺度关注

摘要

The invention discloses a deep network lung texture recognition method combined with multi-scale attention, which belongs to the field of image processing and computer vision. In order to accurately recognize the typical texture of diffuse lung disease in computed tomography (CT) images of the lung, a unique attention mechanism module and multi-scale feature fusion module were designed to construct a deep convolutional neural network combing multi-scale and attention, which achieves high-precision automatic recognition of typical textures of diffuse lung diseases. In addition, the proposed network structure is clear, easy to construct, and easy to implement.
机译:本发明公开了一种深度网络肺纹理识别方法,结合多尺度关注,属于图像处理和计算机视野的领域。 为了准确地识别肺的计算机断层扫描(CT)图像中弥漫性肺病的典型质地,设计了独特的注意机构模块和多尺度特征融合模块,用于构建深度卷积神经网络,梳理多尺度和注意力 ,实现高精度的自动识别衍射肺病的典型纹理。 此外,所提出的网络结构清晰,易于构造,易于实现。

著录项

  • 公开/公告号US2021390338A1

    专利类型

  • 公开/公告日2021-12-16

    原文格式PDF

  • 申请/专利权人 DALIAN UNIVERSITY OF TECHNOLOGY;

    申请/专利号US202017112367

  • 发明设计人 RUI XU;XINCHEN YE;HAOJIE LI;LIN LIN;

    申请日2020-12-04

  • 分类号G06K9/62;G06K9/40;G16H50/20;G06N3/08;G16H30/40;

  • 国家 US

  • 入库时间 2022-08-24 22:51:31

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