2D/3D registration based on biplanar X-ray and CT images for surgical navigation.

Background And Objectives: Image-based 2D/3D registration is a crucial technology for fluoroscopy-guided surgical interventions. However, traditional registration methods relying on a single X-ray image into surgical navigation systems. This study proposes a novel 2D/3D registration approach utilizing biplanar X-ray images combined with computed tomography (CT) to significantly reduce registration and navigation errors. The method is successfully implemented in a surgical navigation system, enhancing its precision and reliability.

Methods: First, we simultaneously register the frontal and lateral X-ray images with the CT image, enabling mutual complementation and more precise localization. Additionally, we introduce a novel similarity measure for image comparison, providing a more robust cost function for the optimization algorithm. Furthermore, a multi-resolution strategy is employed to enhance registration efficiency. Lastly, we propose a more accurate coordinate transformation method, based on projection and 3D reconstruction, to improve the precision of surgical navigation systems.

Results: We conducted registration and navigation experiments using pelvic, spinal, and femur phantoms. The navigation results demonstrated that the feature registration errors (FREs) in the three experiments were 0.505±0.063 mm, 0.515±0.055 mm, and 0.577±0.056 mm, respectively. Compared to the point-to-point (PTP) registration method based on anatomical landmarks, our method reduced registration errors by 31.3%, 23.9%, and 26.3%, respectively.

Conclusion: The results demonstrate that our method significantly reduces registration and navigation errors, highlighting its potential for application across various anatomical sites. Our code is available at: https://github.com/SJTUdemon/2D-3D-Registration.