Automatic identification method, device and electronic equipment for hypoplasia of pulmonary interlobar fissures

By performing image analysis and region division on lung CT images, identifying the CT voxel collection in the interlithic region of the lung lobe, the problem of low efficiency and accuracy of identifying interlobular fissures in the prior art is solved, and a more efficient and accurate recognition effect is achieved.

CN117853439BActive Publication Date: 2025-03-18SUZHOU ZHENMIAOJING MEDICAL TECH CO LTD
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Patent Information

Application Number
CN202311843602.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-12-28
Publication Date
2025-03-18
Estimated Expiration
2043-12-28

AI Technical Summary

Technical Problem

The prior art relies on the empirical judgment of doctors when identifying interlobular fissures, resulting in low recognition efficiency and poor accuracy.

Method used

By performing image analysis and processing on the patient's lung CT images, bronchial and pulmonary artery images are determined, and region division is performed based on these images, CT voxel sets in the interlithic region of the lung lobe space are extracted, and target voxel sets in the region of interest are determined by traversing the difference in CT value between characteristic points, and parameter identification processing is performed to determine the development status of interlobular fissures.

Benefits of technology

It significantly improves the recognition efficiency and accuracy of interlobular fissure insufficiency and reduces the dependence on doctors' experience.

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Abstract

The present invention provides an automatic identification method, device and electronic device for pulmonary fissure hypoplasia, which relates to the field of medical technology, including: performing image analysis processing on the patient's lung CT image to determine the bronchial image and pulmonary artery image of the patient's lung; based on the bronchial image and pulmonary artery image, performing regional division processing on the lung CT image to determine the lobe image and the lobe space area between each lobe in the lobe image; extracting the CT voxel set contained in the lobe space area, and determining the target voxel set of the region of interest of pulmonary fissure hypoplasia by traversing the absolute value of the CT value difference corresponding to each feature point in the CT voxel set; performing parameter identification processing on the target voxel set to determine the developmental state of the pulmonary fissure. The present invention can significantly improve the recognition efficiency and recognition accuracy of pulmonary fissure hypoplasia.
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