Fully Automated Brain Surgery Planning with Computational Geometry

An application for computer-assisted surgery planning is presented. The application requires a volumetric image that is annotated with 1) a set of labels representing different structural or functional regions in the image, and 2) one numeric weight per label that provides information about the relative safety of travelling through that region. The application completes a number of preprocessing steps and uses a geometry-based algorithm to generate a list of safe paths through the domain. The paths can then be manually verified using the application’s visualization software. The surgery planning application is available at https://github.com/myociss/freesurgery. Simple instructions for installation and use can be found at the link. This paper suggests a fully automated brain surgery planning pipeline, including automatic labeling; however, the surgery planning software provided is applicable to any multilabel volumetric data in the required format. The surgery planning software depends on a hybrid C++/Python library to find paths, which is available at https://github.com/myociss/pathfinder. This library can also be installed independently for use by any Python application that requires the computation of safe paths through a three-dimensional domain represented by weighted tetrahedral mesh.