Method and device for training classification network for medical images

Abstract

The invention aims to provide online training of a classification network for medical images. The method comprises: aiming at a target disease, obtaining a chest orthotopic image and a corresponding diagnosis report; according to the chest orthotopic image, positioning a heart and lung area in the chest orthotopic image; and inputting the image of the cardio-pulmonary region and the disease information in the corresponding diagnosis report into a classification network as sample data so as to carry out online training. According to the invention, on the basis that the offline trained medical image classification network is used, in an actual scene used by a medical image classification network, through an online learning mode, for example, new medical images and diagnosis report data are further obtained from a medical image database of a hospital for training, so the efficiency of the classification network model is further evolved and improved, the classification network model is more suitable for practical application scenes and crowds, the training precision is improved by introducing disease position information, and the performance of the classification network and the effectiveness of online learning are remarkably improved.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a technique for training a classification network used for medical images. Background technique [0002] Chest X-ray radiation is the most common method for the diagnosis of cardiothoracic diseases and is widely used clinically. In the prior art, the diagnosis by X-ray contrast still needs to rely on manual reading. Manual film reading has high requirements on the personal experience and ability of doctors; at the same time, manual film reading also has problems such as high cost, time-consuming, and easy to be interfered by human factors such as the doctor's status. [0003] With the rapid development of artificial intelligence, especially in the field of deep learning, a large number of researchers have tried to use this type of technology to help solve the diagnostic problems of medical imaging. When the neural network used for medical diagnosis obtained by ...

AI Technical Summary

Problems solved by technology

In the implementation process, the above schemes often only obtain the disease types corresponding to the images through simple keyword retrieval, but do not make full use of the key information of the location of the disease, resulting in poor performance of online learning

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