Estimating brain-surface deformation using stereo-camera and thin-plate spline

This study proposes a method to estimate brain-surface deformation, which usually happens during cranium removal for brain surgery. The deformation estimation method utilizes a stereo-vision camera system to estimate brain surface structure and adopts thin-plate spline algorithm (TPS) to model the brain deformation. Before brain deformation, the full brain surface needs to be reconstructed by using pre-operative medical images or surface digitizing devices. Next, feature points on the surface are detected and reconstructed into 3-D shape from the images obtained by the stereo-vision cameras. While the deformation occurs, we estimate the corresponding points of the feature points in the current images. By associating the feature points before and after brain deformation, a globally smooth transformation can be estimated by TPS. The transformation is then applied to the full surface data, and the deformed brain surface is thus obtained. In the experiment, a porcine brain is used as the phantom to test the proposed method, and the result shows the average mean error is below 1.1 mm, which proves the superiority of this approach.