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Cited by 316

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An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization

Grimson, W.E.L., Ettinger, G.J., White, S.J., Lozano-Perez, T., Wells, W.M., Kikinis, R.·1996·IEEE Transactions on Medical Imaging

Abstract

There is a need for frameless guidance systems to help surgeons plan the exact location for incisions, to define the margins of tumors, and to precisely identify locations of neighboring critical structures. The authors have developed an automatic technique for registering clinical data, such as segmented magnetic resonance imaging (MRI) or computed tomography (CT) reconstructions, with any view of the patient on the operating table. The authors demonstrate on the specific example of neurosurgery. The method enables a visual mix of live video of the patient and the segmented three-dimensional (3-D) MRI or CT model. This supports enhanced reality techniques for planning and guiding neurosurgical procedures and allows us to interactively view extracranial or intracranial structures nonintrusively. Extensions of the method include image guided biopsies, focused therapeutic procedures, and clinical studies involving change detection over time sequences of images.

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Metadata

Authors
Grimson, W. E. L., Ettinger, G. J., White, S. J., Lozano-Perez, T., Wells, W. M., & Kikinis, R.
Venue
IEEE Transactions on Medical Imaging
Published
1996-04
Volume
15
Issue
2
Pages
129-140
ISSN
0278-0062 (ISSN-L)
OpenAlex
W2118027260
Cited by
316
References
0
FWCI
32.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization. https://app.cochat.ai/papers/10.1109/42.491415
The paper
Grimson, W. E. L., Ettinger, G. J., White, S. J., Lozano-Perez, T., Wells, W. M., & Kikinis, R. (1996). An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/42.491415

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.