Neural network model training method, device and system

Abstract

The invention discloses a neural network model training method, device and system and belongs to the image processing field. The method comprises the following steps that: medical samples sent by a plurality of clients are received, wherein the medical sample sent by the first client comprises a plurality of CT images and first label images corresponding to each CT image, wherein the first label images are used for identifying specified organs contained in the CT images, the first client adopts a local neural network model to segment the plurality of CT images so as to form the first label images, and the first client is any one client in the plurality of clients; and a first neural network model in a server is trained according to the medical samples sent by the plurality of clients, wherein the first neural network model is a neural network model of the latest version in the server. With the neural network model training method, device and system of the invention adopted, the training time of the neural network model is shortened, and the accuracy of the training of the neural network model is effectively improved. The neural network model training method, device and system of the present invention are used for training neural network models.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a neural network model training method, device and system. Background technique [0002] Image segmentation is a technology that divides an image into several specific regions with unique properties and extracts objects of interest. It is a key step from image processing to image analysis. [0003] Currently, in the medical field, a neural network model can be used to segment medical images, and the neural network model can be obtained by training an initial neural network model using predetermined training samples (for example, the steepest descent method can be used for training). Specifically, the server can pre-collect a large number of training samples offline, each training sample includes the original image and the segmentation result of the original image, and use the multiple training samples to train the original neural network model to obtain the trained neural network...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems of long training time and low training accuracy of the neural network model in the prior art, the embodiment of the present invention provides a neural network model training method, device and system

Images