2D/3D Multimode Medical Image Registration Based on Normalized Cross-Correlation
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Technologies in Various Fields · Photoacoustic and Ultrasonic Imaging · Image Enhancement Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China
Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
Funding
Sichuan Science and Technology Program
References (53)
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