Biomedical PaPer Remote Computing Environment Compensating for

Objective: Anatomical and functional image data become invalid during an operation due to brain shift. Compensation is achieved by using intraoperative imaging to update anatomical information. To accelerate the registration and visualization of pre- and intraoperative image data, the presented work focuses on remote computing capabilities. The underlying hework efficiently combines local desktop computers and remote high-end graphics workstations exploiting expensive hardware. .Methods: By performing a11 computations on the remote computer, the MR volumes are rigidly aligned via voxel-based registration. Using ,gaphics hardware for acceleration, dl interpolation operations are performed with 3D texzure-mapping hardware. .4 new approach then transforms functional markers from preoperative measurements to the intraoperative situation using an automatic tracking algorithm to identify corresponding sulci. Communicating Java viewers are suggested for analyzing the results interactively on a local computer, with all calculations being performed exclusively on the remote computer. Results: The suggested approach was successfully applied in 5 cases using -MR data containing functional markers of MEG and f;MRI measurements identi~ng eloquent brain areas. Remote large-scale graphics hardware was thereby efficiently made available for fast registration and interactive direct volume rendering in neurosurgery. Conclusion: Overall, the presented framework demonstrates efficient access of expensive highend hardware remotely controlled by thin clients, and further emphasizes the need to compensate for

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