* Corresponding author. Tel.: #49-9131-85-29923; fax: #49-9131-85-29931. E-mail address: hastreiter@informatik.uni-erlangen.de (P. Hastreiter). Computers & Graphics 24 (2000) 385}389 Data Visualization Registration techniques for the analysis of the brain shift in neurosurgery P. Hastreiter*, C. Rezk-Salama, C. Nimsky, C. Lu K rig, G. Greiner, T. Ertl Computer Graphics Group, IMMD IX, Am Weichselgarten 9, 91058 Erlangen, Germany Department of Neurosurgery, Schwabachanlage 6, 91054 Erlangen, Germany Visualization and Interactive Systems Group, Breitwiesenstr. 20-22, 70565 Stuttgart, Germany Abstract 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 e$cient 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  2000 Elsevier Science Ltd. All rights reserved. Keywords: Brain shift; Registration; Volume visualization; Neurosurgery; Deformable surfaces; 3D texture mapping; Adaptive subdivision 1. Introduction The comprehensive diagnosis of diseases and lesions is considerably assisted by di!erent tomographic imaging modalities like computed tomography (CT) and mag- netic resonance imaging (MRI), since they provide vari- ous information and improve the spatial understanding of anatomical structures. Integrating such data into an operation with a target in the center of the brain makes the access easier and tremendously reduces the risk of hitting critical structures. Due to the rigid behavior of the skull it is possible to de"ne a reliable transformation between the image data and the head of the patient in the beginning of an operation using a neuro-navigation sys- tem. Thereby, showing the position of an instrument in relation to the image data, it is intended to predict structures which are approached. However, depending on the drainage of cerebrospinal #uid and the movement or removal of tissue, the initial shape of the brain changes and leads to the brain shift phenomenon which results in great inaccuracies during the ongoing course of the op- eration [1]. Therefore, it is important to understand the correlation of all e!ects and to correct the shift of the brain. Data sets showing the head of the patient before and after the shift of the brain has occurred represent an important prerequisite of the analysis. Currently, they are mainly obtained with magnetic resonance scanners [2] or to a more limited range with ultrasound devices [3]. In order to obtain a more comprehensive insight into the brain shift phenomenon two registration approaches were implemented. As presented in Section 2, deformable surfaces are used to generate models of the brain surface in the pre- and the intra-operative stage. Color encoding after e$cient distance calculation further enhances the CAG=818=Susan=Venkatachala=BG 0097-8493/00/$ - see front matter  2000 Elsevier Science Ltd. All rights reserved. PII: S 0 0 9 7 - 8 4 9 3 ( 0 0 ) 0 0 0 3 4 - 0