Using three-dimensional multigrid-based snake and multiresolution image registration for reconstruction of cranial defect

Abstract

In cranioplasty, neurosurgeons use bone grafts to repair skull defects. To ensure the protection of intracranial tissues and recover the original head shape for aesthetic purposes, a custom-made pre-fabricated prosthesis must match the cranial incision as closely as possible. In our previous study (Liao et al. in Med Biol Eng Comput 49:203-211, 2011), we proposed an algorithm consisting of the 2D snake and image registration using the patient's own diagnostic low-resolution and defective high-resolution computed tomography (CT) images to repair the impaired skull. In this study, we developed a 3D multigrid snake and employed multiresolution image registration to improve the computational efficiency. After extracting the defect portion images, we designed an image-trimming process to remove the bumped inner margin that can facilitate the placement of skull implants without manual trimming during surgery. To evaluate the performance of the proposed algorithm, a set of skull phantoms were manufactured to simulate six different conditions of cranial defects, namely, unilateral, bilateral, and cross-midline defects with 20 or 40% skull defects. The overall image processing time in reconstructing the defect portion images can be reduced from 3 h to 20 min, as compared with our previous method. Furthermore, the reconstruction accuracies using the 3D multigrid snake were superior to those using the 2D snake.