How does adding anatomical landmarks as fiducial points in the point-matching registration of neuronavigation influence registration accuracy?

Abstract

Abstract Skin markers (SMs) are usually used as fiducial points in registration of neuronavigation, but the areas in which they can be adhered to are restricted, which usually results in poor distribution of the SMs and a large registration error. In this research, we studied whether the registration accuracy can be improved by adding anatomical landmarks (ALs), which are thought to have a larger localization error than SMs. A series of random SM configurations were generated, and for each SM configuration, we generated a corresponding SM-AL configuration by adding several ALs. We then compared the accuracy of the point-matching registration of the SM configurations with that of the corresponding SM-AL configurations. Experiment results indicated that adding ALs always made the mean target registration error of the whole head fall into a lower and narrower range, which meant that the registration became more accurate and more stable. In addition, adding more ALs resulted in a better performance.