Publication Details
Nikos Chrisochoides, Andriy Fedorov, Andriy Kot, Neculai Archip, Daniel Goldberg-Zimring, Dan Kacher, Stephen Whalen, Ron Kikinis, Ferenc Jolesz, Olivier Clatz, Simon K. Warfield, Peter Black and Alexandra Golby.
Published in International Conference on Computational Science (ICCS 2007), pages 980 -- 987, 2007
Abstract
In this paper we present our experience with an Image Guided Neurosurgery Grid-enabled Software Environment (IGNS-GSE) which integrates real-time acquisition of intraoperative Magnetic Resonance Imaging (IMRI) with the preoperative MRI, fMRI, and DT-MRI data. We describe our distributed implementation of a non-rigid image registration method which can be executed over the Grid. Previously, non-rigid registration algorithms which use landmark tracking across the entire brain volume were considered not practical because of the high computational demands. The IGNS-GSE, for the first time ever in clinical practice, alleviated this restriction. We show that we can compute and present enhanced MR images to neurosurgeons during the tumor resection within minutes after IMRI acquisition. For the last 12 months this software system is used routinely (on average once a month) for clinical studies at Brigham and Women’s Hospital in Boston, MA. Based on the analysis of the registration results, we also present future directions which will take advantage of the vast resources of the Grid to improve the accuracy of the method in places of the brain where precision is critical for the neurosurgeons.
