The accuracy of image-guided neurosurgery generally suffers from brain deformations due to intraoperative changes, e.g., brain shift or tumor resection. In order to improve the accuracy, we developed a biomechanical model of the human head which can be employed for the correction of preoperative images. By now, the model comprises two different materials. The correction of the preoperative image is driven by a set of given landmark correspondences. Our approach has been tested using synthetic images and yields physically plausible results. Additionally, we carried out registration experiments with a preoperative MR image and a corresponding postoperative image simulating an intra-operative image. We found, that our approach yields good prediction results, even in the case when correspondences are given in a small area of the image only.
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