A Dynamic Data Driven Grid System for Intra-operative Image Guided Neurosurgery*

Amit Majumdar1, Adam Birnbaum1, Dong Ju Choi1, Abhishek Trivedi2, Simon K. Warfield3, Kim Baldridge4,1, and Petr Krysl2

1San Diego Supercomputer Center, La Jolla, CA 92093, USA

2Structural Engineering Department, University of California San Diego, La Jolla, CA 92093, USA

3Computational Radiology Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 11111 USA

4Department of Chemistry, University of Zurich

Abstract. In the future, advanced biomechanical simulations of brain deformation during surgery will require access to multi-teraflop parallel hardware, supporting operating room infrastructure. This will allow surgeons to view images of intra-operative brain deformation within the strict time constraints of the surgical procedure - typically on the order of minutes, multiple times during a six or eight hour long surgery. In this paper we explore the grid infrastructure issues involved in scheduling, on-demand computing, data transfer and parallel finite element biomechanical simulation, which would guarantee that such a dynamic data driven real time application is actually feasible.

This research was supported in part by the NSF ITR grants CNS 0427183, 0426558, and NIH grants P41 RR13218, P01 CA67165, R01 LM0078651.

LNCS 3515, pp. 672-679.

Last modified: