NDI-based neurosurgery department navigation registering testing method and system

Abstract

The invention provides a NDI-based neurosurgery department navigation registering testing method and a system. The method comprises the steps of performing three-dimensional scanning on a patient head, obtaining a preoperative image, obtaining a 3D model based on preoperative image processing, marking the 3D model, forming a marking point, printing the 3D model which is provided with the marking points, obtaining a 3D printing model and recording the 3D printing model as a body membrane; performing coordinate system registering by means of an optical positioning device NDI; based on a dissection characteristic point, respectively performing rough registering and precise registering, thereby finishing preoperative or in-surgery registering; recording the coordinates of all marking points onthe body membrane by means of a probe tool of NDI, and calculating preoperative or in-surgery registering precision. Through utilizing Goicp, a better registering result can be obtained and registering precision is improved. A head three-dimensional model can be obtained through a simple step. No other operation is required. Simple operation method and easy popularization are realized. Recesses are dug on a manually manufactured model and 3D printing is performed. The registering precision can be simply and quickly tested.

Description

technical field [0001] The invention relates to the technical field of medical image processing and application, in particular to an NDI-based neurosurgery navigation registration test method and system. Background technique [0002] During neurosurgery, it is one of the most important steps to align the preoperative CT data to the position of the patient during the operation. The traditional coarse registration based on anatomical feature points-icp fine registration method may fall into local optimum during fine registration due to the unsatisfactory coarse registration effect, which affects the overall registration effect. Methods based on implanted markers require additional surgical steps and cause additional trauma to the patient. The method of intraoperative data acquisition by 3D scanner requires the design of a whole complex system. However, the registration using the Gaussian mixture model needs to segment the characteristic area of ​​the 3D image and then regist...

AI Technical Summary

Problems solved by technology

The above-mentioned patent documents can effectively improve the registration accuracy. This method does not use coarse registration based on anatomical feature points, but in actual operation, this method may cause the two midlines obtained due to the offset of the binary image centroid to fall on the It is difficult to use the probe to accurately collect point sets, which affects the implementation of subsequent steps

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