X ray perspective view calibration method in operation navigation system
A technique of surgical navigation and calibration method, which is applied in the field of X-ray fluoroscopic image calibration in a spinal surgery navigation system, can solve the problems of limiting the functional application of a C-arm X-ray machine, affecting the flexibility of surgical navigation, and the stability to be improved, etc. To achieve the effect of convenient clinical application, difficult to estimate deformation, and reliable algorithm
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Embodiment 1
[0019] 1. X-ray fluoroscopy image acquisition and preprocessing
[0020] Use video acquisition technology to digitize X-ray perspective images, and use multi-frame average filtering and wavelet transform methods to comprehensively suppress noise. Firstly, multiple images are superimposed and averaged, and then the averaged image is used as the input image for wavelet transform filtering. The type of wavelet adopts the symmetric wavelet symN proposed by Daubechies, N=2,3,...8, and adopts soft thresholding and fixed threshold criterion for denoising. After the above series of processing, the image noise is effectively filtered out and the detailed information in the original image is better preserved.
[0021] 2. Mark point recognition and correction
[0022] First, filter the background information. Using the principle of digital subtraction: set the original image as I Source , Using the kernel function with the diameter of the marker point as the size to compare I Source Perform ...
Embodiment 2
[0085] Example 2 Collection and calibration test of clinical fluoroscopy images
[0086] The calibration target is fixed on the image intensifier of the C-shaped wall X-ray machine, and the proximal target surface is close to the input screen of the intensifier to collect the patient's fluoroscopy image. Taking into account the sampling time and the movement of the patient's body, the present invention superimposes and averages the images collected within 0.5 seconds after the fluoroscopic pedal is released, and performs wavelet filtering;
[0087] Automatically recognize the marked points, the kernel function of the median filter is 2.5mm; the present invention uses filtering and subtraction methods to remove the information of non-marked points in the image. In the template matching algorithm, with 0.85 as the threshold, all points with R(i,j)>0.85 are listed as possible marker point centers, clustering is performed to find the class center, and then the marker is obtained by th...
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