Segmented naming method and system for lung tracheas and blood vessels

Abstract

The embodiment of the invention provides a segmented naming method and system for lung tracheas and blood vessels, and the method comprises the steps: extracting a trachea center line of a lung, and building a trachea tree structure according to the trachea center line; lung lobe type division is carried out on the trachea of each branch in the trachea tree structure; and classifying the lung segment of each bronchial tube by adopting a first classifier corresponding to the lung lobe type of the trachea to obtain a lung segment naming result of each bronchial tube. According to the embodimentof the invention, the tracheal center line of the lung is extracted; establishing tracheal tree structure, according to the lung segment naming method, the lung segment of each bronchus is classifiedby adopting the first classifier corresponding to the lung lobe type of the trachea, and the lung segment naming result of each bronchus is obtained, so that the lung trachea can be automatically named segment by segment through the effectively established spatial topological structure of the human tubular organ, the segment naming efficiency is improved, and the error rate is reduced.

Description

technical field [0001] The present invention relates to the field of medical image processing, in particular to a method and system for segmental naming of pulmonary trachea and blood vessels. Background technique [0002] Lung cancer is the most threatening tumor to human life and health. Whether it is early screening of lung cancer or preoperative planning of tumor resection, three-dimensional reconstruction and visualization of pulmonary nodules and lung tissue are important methods. The location of the tumor in the lung segment is of great help to the doctor in accurately assessing the lesion and preoperative planning. However, in the prior art, mainstream software such as Mimics does not have such functions. However, the 3D reconstruction and visualization of lung tissue mainly focuses on the segmentation and reconstruction of trachea and blood vessels. Most of the anatomical segmentation and naming of trachea and blood vessels are done manually, which has the defects ...

AI Technical Summary

Problems solved by technology

However, in the prior art, mainstream software such as Mimics does not have such functions

However, the 3D reconstruction and visualization of lung tissue mainly focuses on the segmentation and reconstruction of trachea and blood vessels. Most of the anatomical segment naming of trachea and blood vessels is done manually, which has the defects of low efficiency and error-prone

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