Medical image non-rigid registration algorithm performance evaluation method based on segmentation

Abstract

The invention relates to a medical image non-rigid registration algorithm performance evaluation method based on segmentation. The method concretely comprises the steps that (1) a fixed image is selected, template image registration is performed through a pending evaluation algorithm to obtain a target image, and the manual segmentation image of the target image is segmented into N parts composed of omega1, omega2,...omegan respectively; (2) values of Jacobian determinants of all body pixels of the post-registration image are calculated; (3) the coordinates of the body pixels in all segmented regions are extracted by utilizing a split image IS of the template image I; (4) the coordinates of the body pixels of the corresponding segmented regions of the target image are extracted, the values of the Jacobian determinants of all the body pixels in all the regions are figured out, one is subtracted from each value, and then the values are added and then averaged to obtain regional Jacobian determinant standard values; (5) square averaging is performed on all the regional Jacobian determinant standard values, so that evaluation parameters JSD are obtained, and the performance of the pending evaluation algorithm is judged. Compared with the prior art, the method has the advantage that the image tissue volume changes before and after the registration can be directly reflected.

Description

technical field [0001] The invention relates to the field of image registration in image processing, in particular to a method for evaluating the performance of a segmentation-based non-rigid registration algorithm for medical images. Background technique [0002] The goal of image registration is to find an optimal geometric transformation to make the two registered images consistent in spatial position. The process of registration is to map each point in one image to the corresponding point in another image to achieve a good correspondence between the same structures in the two images. This correspondence is expressed by the spatial deformation field obtained through registration. [0003] Medical image registration technology has been studied for decades, and researchers have proposed many kinds of registration algorithms. Algorithms can be divided into two categories: rigid registration algorithms and non-rigid registration algorithms. Among them, the rigid registratio...

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Most of them quantitatively analyze the information between the points of the fixed image and the template image, a

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