Registration techniques for the analysis of the brain shift in neurosurgery

The brain shift is a phenomenon that occurs during surgical operations on the opened head. It is a deformation of the brain which prohibits exact navigation with pre-operatively acquired tomographic scans since correlation between the image data and the actual anatomical situation invalidates quickly after opening the skull. In order to analyze the brain shift nonlinear registration of two data sets is performed. Thereby, one data set is obtained before and the other during the operation with an open magnetic resonance scanner. Using registration based on deformable surfaces, models of the pre- and the intra-operative brain are obtained. After efficient distance calculation color encoding of the models gives quantitative information. For further anatomical orientation these models are integrated into a representation of the data produced with direct volume rendering. Additionally, we suggest a voxel-based approach based on maximizing mutual information. This accounts for deformations of deeper lying structures considering the volume. Adaptively subdividing the data into piecewise linear patches and using 3D texture mapping, fast evaluation of the non-linear deformation is achieved