Model generation method, medical image segmentation method and device, equipment and medium

Abstract

The embodiment of the invention discloses a model generation method, a medical image segmentation method and device, equipment and a medium. The model generation method comprises the steps of obtaining a sample image of a sample chest, a lung mask image of a known lung in the sample image, and shape priori knowledge of the lung mask image; taking the sample image, the lung mask image and the shapepriori knowledge as a group of training samples, and training the original segmentation model based on multiple groups of training samples to generate a lung segmentation model, wherein the originalsegmentation model comprises a feature extraction network, and an image segmentation network and a priori knowledge regression network which are respectively connected with the feature extraction network. According to the technical scheme of the embodiment of the invention, the problem that the existing segmentation model does not effectively utilize the shape priori knowledge of the lung region is solved, and the priori knowledge regression network set based on the shape priori knowledge is matched with the existing image segmentation network, so that the matching degree of the lung segmentation model and lung region segmentation is improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of medical image processing, and in particular to a model generation method, a medical image segmentation method, a device, a device, and a medium. Background technique [0002] X-ray imaging technology is the most commonly used imaging method in medical examination due to its small radiation dose and low cost. Chest X-rays obtained based on X-ray imaging technology can be used to study various structures in the thoracic cavity. It is an important reference factor for medical staff to diagnose emphysema, lung cancer, tuberculosis, emphysema, pneumothorax, heart disease, pneumoconiosis and other clinical diseases. Therefore, accurately segmenting lung regions from X-ray chest films plays a vital role in the subsequent medical image analysis process. [0003] However, there are many difficulties and challenges in accurately segmenting lung regions from X-ray chest films. First, the shap...

AI Technical Summary

Problems solved by technology

However, these network models do not take into account the unique characteristics of the lung region when they are set up, and they use the same network structure for almost all segmentation tasks, which makes the segmentation accuracy of the lung region need to be improved

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