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Non-rigid medical image anti-rotation registration method based on ellipsoidal model

An ellipsoid model, medical image technology, applied in the field of image processing and medical image registration, can solve the problems of incompatibility with large-angle transformation, slow registration speed, poor anti-rotation, etc., achieve good anti-rotation, improve registration The effect of reducing speed and time consumption

Inactive Publication Date: 2017-08-11
DALIAN UNIVERSITY OF FOREIGN LANGUAGES
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Problems solved by technology

[0012] In order to overcome the problems of poor anti-rotation existing in existing medical image registration methods, inadaptability to large-angle transformations, and slow registration speed, the present invention provides a non-rigid anti-rotation registration method for medical images based on an ellipsoid model

Method used

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  • Non-rigid medical image anti-rotation registration method based on ellipsoidal model
  • Non-rigid medical image anti-rotation registration method based on ellipsoidal model
  • Non-rigid medical image anti-rotation registration method based on ellipsoidal model

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Embodiment

[0065] See attached Figure 8 to attach Figure 20 . The standard image CT1109 in the Visual Human image library was selected as the original reference image (attached Figure 8 ), image PD1110 is used as the original image to be registered (attached Figure 9 ).

[0066] Carry out edge detection operations based on wavelet transform on images CT1109 and PD1110 respectively. After extracting the characteristic rectangular domain of the image, select n=64. The reference image and the image to be registered based on the ellipsoid model are respectively shown in the attached Figure 10 And attached Figure 11 As shown, the registered image after Fourier rotation transformation is shown in the attached Figure 12 shown.

[0067] Select n=16, the reference image and the image to be registered based on the ellipsoid model are respectively shown in the attached Figure 13 And attached Figure 14 As shown, the registered image after Fourier rotation transformation is shown in ...

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Abstract

The invention discloses a non-rigid medical image anti-rotation registration method based on an ellipsoidal model. The method comprises steps of under a precondition that initial transformation of an image is carried out to obtain the image feature point and the minimum feature rectangular domain, dividing the minimum feature rectangular domain of the image by the ellipsoidal model to obtain the average value of the gray level of the pixels in each partition, and taking the average value as the representative of the pixel gray level of the region; based on the pixel gray level sequence, using the Fourier transform algorithm to obtain the image rotation transformation parameter; subjecting the image to rotation transformation to complete one registration process; and reducing the division parameter of the ellipsoidal model to re-divide and re-transform the image, so as to gradually improve the image registration precision; and repeating the abovementioned steps until the image partition number is 1, and carrying out interpolation of the image to achieve the image registration. Compared with the conventional image registration method, the method provided by the invention is faster in registration speed, higher in precision, and better in robustness.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to the technical field of medical image registration, and in particular relates to a non-rigid medical image anti-rotation registration method based on an ellipsoid model. Background technique [0002] Image registration is the process of matching and superimposing two or more images acquired at different times, with different sensors (imaging devices) or under different conditions (weather, illuminance, camera position and angle, etc.). It is widely used in remote sensing data analysis, computer vision, medical image processing and other fields. [0003] Image registration is a very important technology in image analysis. It mainly seeks a certain transformation to make the corresponding points of the two images reach the same spatial position. Physical mechanisms, differences in patient positioning, changes in imaging parameters, and differences in spatial resolution bet...

Claims

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Application Information

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IPC IPC(8): G06T7/33G06T7/00
CPCG06T7/0012G06T2207/30004
Inventor 陶永鹏刘朝霞顼聪郭鹏刘建鑫
Owner DALIAN UNIVERSITY OF FOREIGN LANGUAGES
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