首页> 外国专利> METHOD AND SYSTEM FOR MULTI-SCALE CELL IMAGE SEGMENTATION USING MULTIPLE PARALLEL CONVOLUTIONAL NEURAL NETWORKS

METHOD AND SYSTEM FOR MULTI-SCALE CELL IMAGE SEGMENTATION USING MULTIPLE PARALLEL CONVOLUTIONAL NEURAL NETWORKS

机译:多并行卷积神经网络的多尺度细胞图像分割方法和系统

摘要

An artificial neural network system for image classification, formed of multiple independent individual convolutional neural networks (CNNs), each CNN being configured to process an input image patch to calculate a classification for the center pixel of the patch. The multiple CNNs have different receptive field of views for processing image patches of different sizes centered at the same pixel. A final classification for the center pixel is calculated by combining the classification results from the multiple CNNs. An image patch generator is provided to generate the multiple input image patches of different sizes by cropping them from the original input image. The multiple CNNs have similar configurations, and when training the artificial neural network system, one CNN is trained first, and the learned parameters are transferred to another CNN as initial parameters and the other CNN is further trained. The classification includes three classes, namely background, foreground, and edge.
机译:一种由多个独立的个体卷积神经网络(CNN)组成的用于图像分类的人工神经网络系统,每个CNN配置为处理输入图像斑块,以计算斑块中心像素的分类。多个CNN具有不同的接受视场,用于处理以同一像素为中心的不同大小的图像块。通过组合来自多个CNN的分类结果来计算中心像素的最终分类。提供了图像块发生器,以通过从原始输入图像中裁剪出不同尺寸的多个输入图像块来生成它们。多个CNN具有相似的配置,并且在训练人工神经网络系统时,首先训练一个CNN,然后将学习到的参数作为初始参数传递给另一个CNN,并进一步训练另一个CNN。分类包括三个类别,即背景,前景和边缘。

著录项

  • 公开/公告号US2019236411A1

    专利类型

  • 公开/公告日2019-08-01

    原文格式PDF

  • 申请/专利权人 KONICA MINOLTA LABORATORY U.S.A. INC.;

    申请/专利号US201716315541

  • 发明设计人 JINGWEN ZHU;YONGMIAN ZHANG;

    申请日2017-08-09

  • 分类号G06K9/62;G06N3/04;G06T3/40;

  • 国家 US

  • 入库时间 2022-08-21 12:07:45

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