title: A deformable digital brain atlas system according to Talairach and Tournoux.
abstract: Brain atlases are valuable tools which assist neurosurgeons during the planning of an intervention. Since a printed atlas book has several disadvantages-among them the difficulty to map the information onto a patient's individual anatomy-we have developed a digital version of the well-established stereotaxic brain atlas of Talairach and Tournoux. Our atlas system is mainly dedicated to assist neurosurgical planning, and its benefits are: (i) a three-dimensional (3D) representation of most brain structures contained in the Talairach atlas; (ii) a nonrigid matching capability which warps the standard atlas anatomy to an individual brain magnetic resonance imaging (MRI) dataset in a few minutes and which is able to take deformations due to tumors into account; (iii) the integration of several sources of neuroanatomical knowledge; (iv) an interface to a navigation system which allows utilization of atlas information intraoperatively. In this paper we outline the algorithm we have developed to achieve 3D surface models of the brain structures. Moreover, we describe the nonrigid matching method which consists of two tasks: firstly, point correspondences between the atlas and the patient are established in an automatic fashion, and secondly these displacement vectors are interpolated using a radial basis function approach to form a continuous transformation function. To generate appropriate target structures for the first of these tasks, we implemented a quick segmentation tool which is capable to segment the cortex and ventricles in less than 5 min. An evaluation shows that our nonrigid approach is more precise than the conventional piecewise linear matching, though it should be further improved for the region around the deep grey nuclei. Summarizing, we developed a Win32 program which permits the convenient and fast application of standardized anatomy to individual brains which potentially contain tumors.
authors.affiliation: Department of Medical Informatics, University of Heidelberg, University of Applied Sciences, Max-Planck-Str. 39, D-74081 Heilbronn, Germany. ganser@fh-heilbronn.de
authors.forename: Klaus A
authors.initials: KA
authors.lastname: Ganser
authors.forename: Hartmut
authors.initials: H
authors.lastname: Dickhaus
authors.forename: Roland
authors.initials: R
authors.lastname: Metzner
authors.forename: Christian R
authors.initials: CR
authors.lastname: Wirtz
mesh_terms: D000465:Algorithms; D000716:Anatomy, Artistic / Q000379:methods; D019412:Anatomy, Cross-Sectional / Q000379:methods; D001921:Brain / Q000033:anatomy & histology* / Q000601:surgery*; D016208:Databases, Factual; D004548:Elasticity; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008488:Medical Illustration; D008953:Models, Anatomic; D038361:Neuronavigation / Q000379:methods*; D010363:Pattern Recognition, Automated; D011856:Radiographic Image Enhancement / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique