Medical image-based focus detection method, model training method and model training device

Abstract

The invention discloses a medical image-based focus detection method. The method is applied to the field of artificial intelligence. The method can be specifically applied to the field of intelligentmedical treatment. The method comprises the steps: obtaining a to-be-predicted molybdenum target image; obtaining a probability value of each pixel point belonging to a focus in the to-be-predicted molybdenum target image through a main task network model, the main task network model being obtained through training of a source domain data set and a domain classification network model, and the domain classification network model being obtained through training of the source domain data set and a target domain data set; and generating a lump detection result of the to-be-predicted molybdenum target image according to the probability value of each pixel point belonging to the focus. The invention further provides a model training method and device. According to the method, the problem of domain difference between the source domain data set and the target domain data set is solved by utilizing the relationship between the main task network model and the domain classification network model.Therefore, the main task network model obtains excellent detection performance on the target data set.

Description

[0001] This application claims the priority of the Chinese patent application submitted to the China Patent Office on January 29, 2019, with the application number 201910087685.0, and the title of the invention is "Medical image-based lesion detection method, model training method and device", the entire content of which Incorporated in this application by reference. technical field [0002] The present application relates to the field of artificial intelligence medical care, and in particular to a method of lesion detection based on medical images, a method and a device for model training. Background technique [0003] Mammography has high spatial resolution and can display the early symptoms of breast cancer. It is recognized as the most reliable and convenient method for early diagnosis of breast cancer. With the rapid development of computer and image processing technology, using computer-aided diagnosis technology to assist clinicians to detect suspicious lesions in ima...

AI Technical Summary

Problems solved by technology

[0006] The embodiment of the present application provides a medical image-based lesion detection method, model training method and device, the relationship between the main task network model and the domain classification network model, and solves the problem between the source domain data set and the target domain data set The problem of domain difference can significantly suppress the domain difference between data sets, so that the trained main task network model can obtain excellent detection performance on the target data set and improve the prediction effect

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