Blood vessel segmentation method based on geodesic distance map and process function equation

A technology of eigenfunction equation and distance map, which is applied in the field of computer vision to achieve the effect of preventing leakage and accurate segmentation

Active Publication Date: 2021-04-13
山东省人工智能研究院
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The main difficulty of this model lies in choosin

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  • Blood vessel segmentation method based on geodesic distance map and process function equation

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[0023] Attached below figure 1 The present invention will be further described.

[0024] A blood vessel segmentation method based on a geodesic distance map and an eigenfunction equation, comprising the steps of:

[0025] a) Construct an asymmetric Finsler metric for vessel segmentation;

[0026] b) Construct a data-driven Randers metric, and further calculate the potential function to be used in the segmentation according to the cost function in the segmentation of the tubular object;

[0027] c) According to the constructed asymmetric Finsler metric, use the fast marching algorithm to solve the geodesic distance map, and calculate the required minimum path length;

[0028] d) Set the stop criterion of the front propagation to prevent leakage and finally get the target object.

[0029]Extend the front propagation based on the geodesic distance map to apply the asymmetric Finsler metric, consider the anisotropy and asymmetry of the boundary at the same time, strengthen the ...

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Abstract

The invention discloses a blood vessel segmentation method based on a geodesic distance map and a process function equation, and the method comprises the steps: enabling the front propagation based on the geodesic distance map to be expanded to the application of an asymmetric Finsler measurement condition, considering the anisotropy and asymmetry of a boundary, strengthening the description of a measurement function, and setting a freezing criterion of the front propagation; the situation of leakage in the anterior propagation process is effectively prevented, smooth anterior propagation is guaranteed, the target object can be found more accurately and quickly, and accurate segmentation of the blood vessel is achieved.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a blood vessel segmentation method based on a geodesic distance map and an eigenfunction equation. Background technique [0002] Since the original level set framework (references: Osher, S., Sethian, J.A.: Fronts propagating with curvature-dependent speed: algorithms based on Hamilton–Jacobi formulations. J. Comput. Phys. 79(1), 12–49 (1988 )) Since it was proposed, the front propagation model has been greatly developed in the application of image segmentation and boundary detection. Due to its strong mathematical background, the front propagation model can be widely applied in the field of computer vision, adaptively processing segmentation and merging in images, etc. Malladi and Sethian proposed a frontier propagation model based on geodesic distance (References: Malladi, R., Sethian, J.A.: A real-time algorithm for medical shape recovery. In: Proceeding of ICCV, pp.304–310( 1...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11
CPCG06T7/0012G06T7/11G06T2207/30101
Inventor 陈达李丽纬
Owner 山东省人工智能研究院
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