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The intraoperative identification of normal and anomalous brain tissue can be disturbed by pulsatile brain motion and movements of the patient and surgery devices. The performance of four motion correction methods are compared in this paper: Two intensity-based, applying optical flow algorithms, and two feature-based, which take corner features into account to track brain motion. The target registration error with manually selected marking points and the temporal standard deviation of intensity were analyzed in the evaluation. The results reveal the potential of the two types of methods.

Intraoperative motion correction in neurosurgery: a comparison of intensity- and feature-based methods