Segmentation method, device and equipment for lung segments and storage medium

Abstract

The invention discloses a segmentation method, device and equipment for lung segments and a storage medium. The method comprises the steps: obtaining a to-be-identified image and a corresponding lunglobe segmentation result; performing lung segment coarse segmentation on the to-be-identified image based on a lung segment coarse segmentation model to obtain a lung region segmentation result; determining a first sub-image corresponding to the lung region segmentation result in the to-be-identified image; determining a second sub-image corresponding to the lung region segmentation result in thelung lobe segmentation result; taking the first sub-image and the second sub-image as input of a dual-channel lung segment fine segmentation model, and performing lung segment fine segmentation on thefirst sub-image based on the dual-channel lung segment fine segmentation model to obtain a first lung segment segmentation result. By means of the technical scheme, lung segment coarse positioning can be rapidly conducted, the data acquisition speed is increased, the fine segmentation of lung segments only needs to be conducted on the lung region segmentation result obtained through coarse segmentation, the segmentation of lung segments is assisted through the lung lobe segmentation result, and the method is more accurate and efficient.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a lung segment segmentation method, device, equipment and storage medium. Background technique [0002] Medical research shows that the symptoms of lung cancer are closely related to the type of lung cancer (including the growth site of the lesion, the size of the lesion, the growth rate, etc.), and the growth site of the lesion is a very important indicator. The bronchi and its branches of each lung segment The distributed lung tissues are called bronchopulmonary segments. By segmenting lung lobes and lung segments in CT images, accurate anatomical structures can be provided for the diagnosis of lung tumors and segmentectomy, and for the diagnosis and surgical treatment of lung cancer. are of great significance. [0003] The existing technology first needs to detect the key point positions of the lung lobes. Based on these detected key point positions, the coor...

AI Technical Summary

Problems solved by technology

This method does not fully consider the differences in lung structure between different patients, and only relies on the detected key points to map the lesion to the pre-made model, and cannot visually display the results on the original image for this patient. It is difficult to evaluate good or bad, so more reliable and efficient solutions need to be provided

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