Automatic spine feature point recognition method based on Gauss curvature flow

A Gaussian curvature and automatic recognition technology, applied in the field of medical image processing, can solve problems such as inaccurate feature points, low data precision, and inaccurate model matching, and achieve high efficiency, high precision, and improved accuracy.

Inactive Publication Date: 2017-06-20
NORTHWESTERN POLYTECHNICAL UNIV
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This method marks inaccurate feature points, resultin

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  • Automatic spine feature point recognition method based on Gauss curvature flow
  • Automatic spine feature point recognition method based on Gauss curvature flow
  • Automatic spine feature point recognition method based on Gauss curvature flow

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[0043] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0044] see figure 1 , a method for automatic recognition of spine feature points based on Gaussian curvature flow, comprising the following steps:

[0045] In step 1, three-dimensional reconstruction is performed on the CT image of the human spine to obtain a three-dimensional model of the vertebral body with required feature points.

[0046] see figure 2 , image 3 , Figure 4 , the spine CT data is enhanced and the threshold value is extracted, and the range of the target vertebra is segmented. The segmentation of the vertebral body can be realized using mimics software, such as Figure 5 , Image 6 shown. In the process of model building, steps such as image enhancement, image threshold segmentation, region growing algorithm, and denoising can be used to ensure the accuracy of the model.

[0047] Step 2, meshing the vertebral body ...

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Abstract

The invention discloses an automatic spine feature point recognition method based on a Gauss curvature flow. Firstly, three-dimensional reconstruction is carried out on a CT image of a human spine, a spine body three-dimensional model in need of feature point annotation is obtained, and mesh generation is carried out on the spine body model obtained in the first step; a certain point on the model is selected manually, and the mean curvature of each vertex in spherical space with the minimal radius to be R around the manual selection point is calculated; and finally, n points with the maximal Gauss curvatures around the manual selection point are selected, the n points with the maximal Gauss curvatures and the selection point are subjected to inner product respectively, and the solved point has the minimal included angle. The accuracy for feature point annotation can be improved, the data measurement accuracy is thus improved, and the accuracy is high, and the realization is easy.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, in particular to an automatic recognition method of vertebra feature points based on Gaussian curvature flow. Background technique [0002] Located in the middle of the back, the spine is the supporting bone of the human body and plays an important role in protecting the internal organs of the human body. Due to changes in people's living and working styles in recent years, people maintain the same posture for a long time, which increases the burden on the spine and increases the incidence of spinal diseases. However, due to the complex structure of the spine and the characteristics of spine surgery itself, spine surgery The difficulty is very high, and it is accompanied by great risks. The precise positioning and registration of the spine model remains an unresolved diagnostic and therapeutic problem. [0003] In the localization and registration of the spine model, the main t...

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Application Information

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IPC IPC(8): G06T7/00G06T7/73G06T17/00
CPCG06T17/00G06T2207/10081G06T2207/30012
Inventor 惠宇武君胜鱼滨贺伟杨柳杜静李航
Owner NORTHWESTERN POLYTECHNICAL UNIV
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