首页> 外国专利> TRAINING NEURAL NETWORKS OF AN AUTOMATIC CLINICAL WORKFLOW THAT RECOGNIZES AND ANALYZES 2D AND DOPPLER MODALITY ECHOCARDIOGRAM IMAGES

TRAINING NEURAL NETWORKS OF AN AUTOMATIC CLINICAL WORKFLOW THAT RECOGNIZES AND ANALYZES 2D AND DOPPLER MODALITY ECHOCARDIOGRAM IMAGES

机译:识别和分析2D和多普勒模态心电图图像的自动临床工作流程的训练神经网络

摘要

A method for training neural networks of an automated workflow performed by a software component executing on a server in communication with remote computers at respective laboratories includes downloading and installing a client and a set of neural networks to a first remote computer of a first laboratory, the client accessing the echocardiogram image files of the first laboratory to train the set of neural networks and to upload a first trained set of neural networks to the server. The process continues until the client and the second trained set of neural networks is downloaded and installed to a last remote computer of a last laboratory, the client accessing the echocardiogram image files of the last laboratory to continue to train the second trained set of neural networks and to upload a final trained set of neural networks to the server.
机译:一种用于训练由在与各个实验室的远程计算机通信的服务器上执行的软件组件执行的自动化工作流的神经网络的方法,该方法包括将客户端和一组神经网络下载并安装到第一实验室的第一远程计算机,客户访问第一实验室的超声心动图图像文件以训练该神经网络集,并将第一训练的神经网络集上载到服务器。该过程一直持续到将客户端和第二组经过训练的神经网络下载并安装到上一实验室的最后一台远程计算机,客户端访问上一实验室的超声心动图图像文件以继续对第二组经过训练的神经网络进行训练并将一组经过训练的最终神经网络上传到服务器。

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