Near-infrared subcutaneous vein segmentation method based on multi-feature clustering

Abstract

The invention designs a near-infrared subcutaneous vein segmentation method based on multi-feature clustering, and can realize the multi-feature extraction and the automatic clustering of a vein. The method comprises the following steps:1) adopting a NiBlack and a morphology algorithm to realize the segmentation of a skin area and edge mirror extension; 2) obtaining a vein similarity diagram, a vein directional diagram, a vein scale diagram and an initial segmentation vein through multiscale IUWT (Isotropic Undecimated Wavelet Transform) and Hessian matrix analysis; 3) extracting and repairing a vein branch center line by adopting the initial segmentation vein and the vein directional diagram, and correcting the position and the direction of the branch center line by adopting a segmentation spline fitting method; 4) on the basis of a vein branch direction, calculating a coordinate mapping relationship between an artwork and a branch outline image, and extracting normalized second-order Gaussian characteristics and vein similarity characteristics after an IUWT enhanced image and the vein similarity image are independently mapped to outline image space; and 5) utilizing the obtained vein characteristics to cluster the outline image into three types including skin, vein and a fuzzy region by adopting a K-means algorithm.

Description

technical field [0001] The invention relates to a subcutaneous vein segmentation method, in particular to a near-infrared subcutaneous vein segmentation method based on multi-feature clustering, which is mainly used in the fields of subcutaneous intravenous injection, vein identification and the like. Background technique [0002] With the continuous research of researchers on invisible spectral imaging technology and spectral imaging characteristics of human tissue structure, infrared spectrum has shown excellent enhancement effect in human tissue imaging, especially in subcutaneous vein imaging. Infrared vein imaging is safer and more convenient than X-ray and ultrasound imaging. The vein enhancement of infrared imaging shows that it is essentially due to the difference in spectral response between blood vessels and skin, which makes it still have stable vein enhancement when it is applied to special populations such as children, the elderly, trauma patients, obese patient...

AI Technical Summary

Problems solved by technology

However, due to the generally poor quality of near-infrared vein images, existing vein segmentation methods often have limitations in the following aspects:

[0005] 1. Due to the unavoidable environmental factors, the resulting non-uniformity of image illumination seriously affects the contrast of veins in different areas, which greatly enhances the difficulty of enhancement, measurement and segmentation of veins in shadow areas;

[0006] 2. Due to the poor imaging quality of near-infrared images, threshold-based segmentation methods based on i

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