Multi-parameter breast magnetic resonance image segmentation method based on dynamic adaptive network

Abstract

The embodiment of the invention provides a multi-parameter breast magnetic resonance image segmentation method based on a dynamic adaptive network, which is applied to the technical field of medical imaging and comprises the following steps: acquiring a multi-parameter magnetic resonance sample image; inputting the multi-parameter magnetic resonance sample image into a to-be-trained image segmentation model, and training the to-be-trained image segmentation model to obtain a trained image segmentation model; acquiring a single-parameter magnetic resonance sample image; inputting the single-parameter magnetic resonance sample image into a trained image segmentation model to test the trained image segmentation model, and when the test is successful, obtaining a trained image segmentation model; obtaining a magnetic resonance image to be identified; and inputting the to-be-identified magnetic resonance image into the trained image segmentation model to obtain information of a breast lesion area in the to-be-identified magnetic resonance image. Therefore, the requirement on the sample image in the training process of the image segmentation model is reduced.

Description

technical field [0001] The invention relates to the technical field of medical imaging, in particular to a multi-parameter breast magnetic resonance image segmentation method based on a dynamic self-adaptive network. Background technique [0002] At present, with the rapid development of network model technology, network models have penetrated into many fields of people's lives. For example, face recognition, image classification, data prediction, etc. are performed through network models. The network model can not only provide great convenience to people's life, but also improve the efficiency of data processing. [0003] However, in the current medical imaging technology field, when training a network model for identifying lesion parts in images captured by patients, the model is often trained and tested through multi-parameter images, resulting in higher requirements for sample images. Contents of the invention [0004] The purpose of the embodiments of the present in...

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Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a multi-parameter breast magnetic resonance image segmentation method based on a dynamic adaptive network to solve the problem that the model can only be trained and tested through multi-parameter images

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