Automatic tracking of intraoperative brain surface displacements in brain tumor surgery

In brain tumor surgery, soft-tissue deformation, known as brain shift, introduces inaccuracies in the application of the preoperative surgical plan and impedes the advancement of image-guided surgical (IGS) systems. Considerable progress in using patient-specific biomechanical models to update the preoperative images intraoperatively has been made. These model-update methods rely on accurate intraoperative 3D brain surface displacements. In this work, we investigate and develop a fully automatic method to compute these 3D displacements for lengthy (~15 minutes) stereo-pair video sequences acquired during neurosurgery. The first part of the method finds homologous points temporally in the video and the second part computes the nonrigid transformation between these homologous points. Our results, based on parts of 2 clinical cases, show that this speedy and promising method can robustly provide 3D brain surface measurements for use with model-based updating frameworks.