Non-rigid medical image registration method based on finite element model

Abstract

The invention belongs to the field of medical image processing and relates to a non-rigid medical image registration method based on a finite element model. The registration method comprises the steps of: carrying out global registration on floating images and reference images, then carrying out finite element modeling on the globally registered images and the reference images and finally computing the energy terms related to the model by adopting a classified registration thought in the registration process, wherein the energy terms comprise an internal energy term and an external energy term which drives the model to deform; and when the total energy of the model is minimum under the control of the internal and external energy terms, the model is converged at an equilibrium position so that the local accurate registration of the images is realized and the registration of the non-rigid images is finally realized. Experiments show that the local deformation of the non-rigid images canbe well simulated by using the method so that the accuracy and the speed of the registration are improved, the robustness of the registration is strengthened and a favorable foundation is laid for the fusion of medical images.

Description

technical field [0001] The invention relates to a method in the technical field of image processing, in particular to a non-rigid medical image registration method based on a finite element model. Background technique [0002] Medical image registration is the basis of medical image fusion and an important technology of medical image analysis. It mainly seeks a spatial transformation to make the corresponding points on two medical images reach the consistency of spatial position or anatomical point. In the process of medical diagnosis, due to practical problems such as the physical mechanism of different modes of images showing different properties, patient movement, changes in imaging parameters, and different spatial resolutions between different imaging devices, it is only necessary for doctors to manually convert two identical or The spatial registration of images of different modes will be subject to many limitations, and often has a large subjectivity, its reliability ...

AI Technical Summary

Problems solved by technology

[0004] The technical defect of the medical image registration method based on image features is that it needs to segment the image to extract the features of the image. Because the structure of non-rigid tissue is very complex, some interfaces are not very obvious, and it usually requires manual pre-selection of features. It is time-consuming and labor-intensive, and the accuracy of registration is affected by the accuracy of segmentation. It is generally difficult to complete automatically, which makes the registration time process slow and the registration accuracy is not high.

[0005] The technical defect of the medical image registration method based on image grayscale information is that it does not need to segment the image, but directly calculates the entire image, which will result in slow registration speed, long registration time, and poor robustness.

[0006] Compared with rigid medical images, non-rigid medical images have larger and more complex deformations, and the existing registration algorithms cannot simulate their deformation well and overcome the time-consuming, low accuracy, and weak robustness of registration. and other shortcomings

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