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Journal Article

Quasi-real-time neurosurgery support by MRI processing via grid computing

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Lippmann,  H.
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Kruggel,  F.
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Lippmann, H., & Kruggel, F. (2005). Quasi-real-time neurosurgery support by MRI processing via grid computing. Neurosurgery Clinics of North America, 16(1), 65-75. doi:10.1016/j.nec.2004.07.009.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-D427-3
Abstract
One problem of providing time-critical medical services over the grid is always its dependency on the Internet. It cannot be assumed that transfer ofa certain amount of data over the Internet is always achieved during a specified period. Such a requirement cannot be fulfilled by the infrastructure of the Web. There is always the risk of a network delay or even an overload. Because of this, another goal of this project is the evaluation of grid services versus the use of local services. A further point for future research related to the chain has to deal with the optimization approach for the linear registration step. Because the optimization uses the downhill simplex algorithm in a nine-dimensional search space, the number of iterations needed to find the optimum can vary dramatically. This makes linear registration the most unpredictable step of the chain in terms of execution time. It cannot be assured that the global optimum is found. Additional work has to be done in validating the registration accuracy, including the examination of the influence of intensity variations between intraoperative images as well as the influence of tumor resection and the presence of the opened skull versus the closed skull in the fluid-based registration.