Mark point-free robust neuro-navigation automatic registration method

A neuronavigation and automatic registration technology, applied in the field of medical image processing and application, can solve the problems of operator inconvenience, increase the registration time, sensitivity to the initial position of the point cloud, etc. The effect of reducing the number of

Pending Publication Date: 2019-07-05
上海复旦数字医疗科技股份有限公司
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Problems solved by technology

This type of method is intuitive, simple, and has high matching accuracy, but it is very sensitive to the initial position of the point cloud. Therefore, most of the neural space navigation methods based on face matching that are currently used in clinical practice require a manual rough registration step in order to provide The next fine registration provides a better initial point cloud position, this step increases the registration time and brings some inconvenience to the operator

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  • Mark point-free robust neuro-navigation automatic registration method
  • Mark point-free robust neuro-navigation automatic registration method
  • Mark point-free robust neuro-navigation automatic registration method

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Embodiment 1

[0056] Example 1 Robust neuronavigation automatic registration test without landmarks

[0057] Realize the present invention through the following steps:

[0058] 1. Registration method based on 3D surface feature extraction and matching

[0059] (1) The patient's CT / MRI image is processed to form a point cloud, and the real-time point cloud of the patient's real world is obtained through a high-precision portable laser scanner;

[0060] (2) Remove external values ​​and downsample the two sets of point clouds to keep the same grid resolution. Divide the entire point cloud into several cube regions whose number meets the resolution requirements and keep only one point in each region;

[0061] (3) Use the Intrinsic Shape Signatures (ISS) algorithm to extract the key points of the point cloud. First, use the eigenvalue decomposition algorithm to obtain the eigenvalue λ of the weighted discrete matrix around each point 1 >λ 2 >λ 3 , which satisfies the formula

[0062]

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Abstract

The present invention belongs to the technical fields of medical image processing and application, and particularly relates to a mark point-free robust neuro-navigation automatic registration method.The registration method uses extraction and matching based on three-dimensional surface features, after a point cloud obtained by a laser scanner and a point cloud obtained by CT/MRI are used to obtain a coordinate transformation between the two point clouds to achieve the coarse registration, the registration method of iteration of the most adjacent points is used, a result of the coarse registration is then subjected to the registration with the point cloud representing a patient space reconstructed by CT in neuro-navigation to realize the automatic registration of the neuro-navigation. Themethod has better robustness and convenience than a neuro-navigation spatial registration method in the prior art based on surface matching.

Description

technical field [0001] The invention belongs to the technical field of medical image processing and application, relates to a neuronavigation registration method, in particular to a robust neuronavigation automatic registration method without marker points. Background technique [0002] The prior art discloses a neuronavigation system as a medical auxiliary positioning device, which can provide doctors with real-time intraoperative information, can effectively make up for the shortcomings of traditional neurosurgery methods, and improve the quality of surgery. The clinical application results show that the core function of the neuronavigation system is to use images to locate and guide surgical instruments. Therefore, the positioning and registration accuracy, robustness and convenience of the real surgical scene and the image-guided space directly affect the neuronavigation system. performance. [0003] Currently, registration methods used in neuronavigation systems are ma...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B34/20G06K9/46G06K9/62
CPCA61B34/20A61B2034/2065G06V10/50G06F18/22
Inventor 安涌张柏林
Owner 上海复旦数字医疗科技股份有限公司
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