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Method for extracting branch points of blood vessel network

An extraction method and branch point technology, which is applied in the field of extraction of branch points of the vascular network, to achieve the effect of improving accuracy and suppressing the influence of noise

Pending Publication Date: 2021-09-21
SHENZHEN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Currently, the widely used vascular network analysis parameters are difficult to characterize the abnormal growth of vascular network, and the characterization of new parameters of vascular network analysis, such as statistical distortion, the number of multi-type vascular segments, etc., largely depends on the key nodes of the blood vessel ( For example, branch point and end point) detection, so how to improve the accuracy of vessel key node extraction has become the focus of attention

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  • Method for extracting branch points of blood vessel network
  • Method for extracting branch points of blood vessel network
  • Method for extracting branch points of blood vessel network

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Embodiment Construction

[0049] The present application provides a method for extracting branch points of a vascular network. In order to make the purpose, technical solution and effect of the present application clearer and clearer, the present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0050]Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, compone...

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Abstract

The invention discloses a method for extracting branch points of a blood vessel network. The method comprises the following steps: acquiring a blood vessel segmentation map of a blood vessel image; based on the blood vessel segmentation map, determining a skeleton feature map corresponding to the blood vessel image; and matching the skeleton feature map with a plurality of preset matching models to obtain branch points corresponding to the blood vessel image. The skeleton feature map is determined based on the blood vessel segmentation image of the blood vessel image, and then each skeleton feature point in the skeleton feature map is matched through the multi-angle matching model to select the branch point in the skeleton feature map, so that the influence of noise in the neighborhood of the branch point can be effectively suppressed, the accuracy of branch point positioning can be improved, and the accuracy of blood vessel network analysis based on the branch points can be improved.

Description

technical field [0001] The present application relates to the technical field of medical image processing, in particular to a method for extracting branch points of a blood vessel network. Background technique [0002] As a commonly used analysis method, medical image processing provides accurate digital quantitative analysis results for the development of vascular network, thereby providing a new criterion for the change of vascular network and the occurrence of diseases. Currently, the widely used vascular network analysis parameters are difficult to characterize the abnormal growth of vascular network, and the characterization of new parameters of vascular network analysis, such as statistical distortion, the number of multi-type vascular segments, etc., largely depends on the key nodes of the blood vessel ( For example, branch point and end point) detection, so how to improve the accuracy of vessel key node extraction has become the focus of attention. Contents of the ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/12G06T7/13G06T7/136G06T7/194G06K9/46
CPCG06T7/0012G06T7/12G06T7/13G06T7/136G06T7/194G06T2207/30101
Inventor 林浩铭周毅智陈冕陈昕陈思平
Owner SHENZHEN UNIV
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