US 12,175,689 B2
Medical image registration method based on progressive images
Erlin Tian, Zhengzhou (CN); Qian Zheng, Zhengzhou (CN); Jiaofen Nan, Zhengzhou (CN); Xiao Zhang, Zhengzhou (CN); and Weide Liang, Zhengzhou (CN)
Assigned to Zhengzhou University of Light Industry, Zhenzhou (CN)
Filed by Zhengzhou University of Light Industry, Zhengzhou (CN)
Filed on Jun. 28, 2022, as Appl. No. 17/851,066.
Claims priority of application No. 202110719973.0 (CN), filed on Jun. 28, 2021.
Prior Publication US 2022/0414903 A1, Dec. 29, 2022
Int. Cl. G06T 7/33 (2017.01); G06T 3/02 (2024.01); G06T 7/37 (2017.01); G06V 10/74 (2022.01)
CPC G06T 7/337 (2017.01) [G06T 3/02 (2024.01); G06T 7/37 (2017.01); G06V 10/761 (2022.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30016 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A two-stage medical image registration method based on progressive images (PIs) comprising the following steps:
step 1: merging a reference image R to be registered with a floating image F to be registered to generate multiple intermediate PIs;
step 2: registering, by a speeded-up robust features (SURF) algorithm and an affine transformation, the floating image F with the intermediate PIs to acquire coarse registration results;
step 3: registering, by the SURF algorithm and the affine transformation, the reference image R with the coarse registration results to acquire fine registration results; and
step 4: comparing the fine registration results of the intermediate PIs acquired in repeating steps 2 and 3 and selecting an optimal registration result as a final registration image,
wherein the multiple intermediate PIs are generated as follows: taking the intermediate progressive image as a reference image for an intermediate registration process and merging the reference image with the floating image F to generate the multiple intermediate PIs; or, taking the intermediate progressive image as a floating image for the intermediate registration process and merging the floating image with the reference image R to generate the multiple intermediate PIs, and
wherein in step 2, the coarse registration result is acquired as follows:
sub-step 1: taking an intermediate progressive image Mk as a reference image and extracting, by the SURF algorithm, feature points of the floating image F and the intermediate progressive image Mk, k=0, 1, 2 . . . l;
sub-step 2: describing the feature points to acquire feature vectors and performing feature point matching based on a similarity of the feature vectors; and
sub-step 3: spatially transforming, by the affine transformation, the floating image F, and calculating, by a least squares (LS) method, a transformation parameter; transforming the floating image F into a coordinate system of the reference image R through the transformation parameter; and registering, by a bicubic interpolation function, the transformed floating image F with the reference image R to acquire an initial registration result described as the coarse registration result.