2D/3D Multimode Medical Image Registration Based on Normalized Cross-Correlation

被引：85

作者：

Liu, Shan ^{[1
]}

Yang, Bo ^{[1
]}

Wang, Yang ^{[1
]}

Tian, Jiawei ^{[1
]}

Yin, Lirong ^{[2
]}

Zheng, Wenfeng ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Automat, Chengdu 610054, Peoples R China

[2] Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA

来源：

APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 06期

关键词：

2D; 3D medical image registration; normalized cross-correlation; differential operator; image processing; 2D-3D REGISTRATION; RECONSTRUCTION; ACCURATE; MODELS; VIEW;

D O I：

10.3390/app12062828

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Image-guided surgery (IGS) can reduce the risk of tissue damage and improve the accuracy and targeting of lesions by increasing the surgery's visual field. Three-dimensional (3D) medical images can provide spatial location information to determine the location of lesions and plan the operation process. For real-time tracking and adjusting the spatial position of surgical instruments, two-dimensional (2D) images provide real-time intraoperative information. In this experiment, 2D/3D medical image registration algorithm based on the gray level is studied, and the registration based on normalized cross-correlation is realized. The Gaussian Laplacian second-order differential operator is introduced as a new similarity measure to increase edge information and internal detail information to solve single information and small convergence regions of the normalized cross-correlation algorithm. The multiresolution strategy improves the registration accuracy and efficiency to solve the low efficiency of the normalized cross-correlation algorithm.

引用

页数：16

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