Vascular image processing method based on circular contour polarity

Abstract

The invention discloses a vascular image processing method based on circular contour polarity and belongs to the technical field of image processing. Two circular contour polarity indexes for judging image area features in terms of geographical structural distribution are provided: first and second circular contour polarity indexes; a noise pollution area and a vascular area in a vascular image can be distinguished and are separately treated by different thresholding methods; the noise pollution area is treated by brightness thresholding and structural thresholding, while the vascular area is treated by only structural thresholding; noise in the vascular image can be effectively removed, and high-quality vascular extraction results are obtained.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a blood vessel image processing method based on the polarity of a circular contour map. Background technique [0002] Vascular images are widely used in medical research and clinical diagnosis, such as quantitative analysis of tumor angiogenesis, diagnosis of diabetic retinopathy, etc. Various techniques are used to generate images of blood vessels, and many imaging methods are in development. Vascular imaging techniques include computed tomography, magnetic resonance angiography, whole-mount electron microscopy, and two-photon fluorescence angiography. New imaging techniques can obtain micron-level resolution and better capture images of small blood vessels (capillaries). The development of these excellent technologies has allowed us to glimpse the structure of blood vessels. Morphological analysis of blood vessels remains challenging due to their topologi...

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Problems solved by technology

However, the parametric descriptions of these algorithms are usually very complicated (such as super ellipsoid, three-dimensional B-spline surface, three-dimensional cylinder model), and the complex branching mode of blood vessels, as well as the approximate error of the shape, also have a great influence on the effect of these algorithms Impact

[0005] Finally, although it is possible to use some complex image processing packages, such as Amira, VidaSuite, VesSeg, instead of the above algorithms, a large number of image processing steps (such as median filtering, Gaussian filtering, image enhancement, erosion, etc.) must be adjusted and modified manually. , expansion and gap filling)

Because a large number of parameters need to be adjusted manually, it leads to a very large workload

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