CT-based three-dimensional jawbone image segmentation modeling method and device and terminal equipment

Abstract

The invention relates to the field of image models, and provides a three-dimensional jawbone image segmentation modeling method based on CT, and the method comprises the steps of constructing a convolutional neural network model; preprocessing the CT image with the segmented and marked jawbone, extracting an image sub-sequence from the CT image as a training sample, and training the convolutionalneural network model to obtain a trained convolutional neural network model, wherein the trained convolutional neural network model is used for obtaining an image sub-sequence extracted from a CT image to be segmented, and obtaining a segmentation result corresponding to the image sub-sequence after processing, wherein the segmentation result is used for obtaining a three-dimensional jaw bone segmentation result of the CT image to be segmented after integration. Meanwhile, the invention further provides a corresponding three-dimensional jaw image segmentation modeling device based on CT, and terminal equipment. The embodiment provided by the invention is suitable for establishing a segmentation model for extracting the three-dimensional jawbone region from the CT image.

Description

technical field [0001] The present invention relates to the field of image models, in particular to a CT-based three-dimensional jaw image segmentation modeling method, a CT-based three-dimensional jaw image segmentation modeling device, a terminal device and a corresponding storage medium. Background technique [0002] As a common fracture with complex structure, maxillofacial fractures are difficult to diagnose only by clinical symptoms and signs, and often require auxiliary diagnosis of imaging. Compared with traditional X-ray films, the three-dimensional images of maxillofacial CT can more clearly and intuitively show the location of fractures and the direction of displacement, and are considered the "gold standard" for the diagnosis of maxillofacial fractures. However, due to the relatively large information contained in CT images, the diagnosis and treatment model based on this method relies on personnel who are proficient in imaging knowledge and professional equipmen...

AI Technical Summary

Problems solved by technology

[0004] In the related technologies of CT-based maxillofacial fracture diagnosis, upper and lower jaw segmentation and three-dimensional visualization are of great significance for facial surgery diagnosis. At present, the main method is semi-automatic way (usually threshold method or region growing method) to segment the upper and lower jaws, the segmentation accuracy of the existing software is poor

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