W.E.L. Grimson 1 ,
G.J. Ettinger 1,3 ,
S.J. White 3 ,
T. Lozano-Pérez 1 ,
W.M. Wells III 1,2 ,
R. Kikinis 2
1Artificial Intelligence Laboratory, Massachusetts
Institute of Technology, Cambridge MA
Abstract:
2 Department of Radiology, Brigham and Womens Hospital,
Harvard Medical School, Boston MA
3The Analytic Sciences Corporation, Reading MA
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. We
have developed an automatic technique for registering clinical data,
such as segmented MRI or CT reconstructions, with any view of the
patient on the operating table, using a series of registration
algorithms, which we demonstrate on the specific example of
neurosurgery. The method enables a visual mix of live video of the
patient with the segmented 3D MRI or CT model, supporting enhanced
reality techniques for planning and guiding neurosurgical procedures,
and to interactively view extracranial or intracranial structures
non-intrusively. Extensions of the
method include image guided biopsies, focused therapeutic procedures
and clinical studies involving change detection over time sequences of images.