Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
Image Guided Surgery
W. Eric L. Grimson
AI Laboratory
Massachusetts Institute of Technology
Monday, Apr 23, 2001, 4:15PM
TCSEQ 201
http://robotics.stanford.edu/ba-colloquium/
Abstract
Minimally invasive procedures promise to revolutionize surgery, by
allowing
surgeons to operate through narrow openings in the body. While these
procedures
in principle reduce the impact on the patient, they impose a burden on
the
surgeon, who must operate while only observing through narrow fields of
view.
To enable surgeons to visualize the entire field, including information
not
visible to the human eye, we provide a set of computer vision tools.
Segmentation methods build patient specific models of anatomy from
medical
scans, utilizing knowledge of standard shapes of structure and their
modes of
variance, as well as knowledge of spatial layout of anatomy.
Registration
methods automatically fuse multi-modal information to a single model,
and align
such models with actual patient position in the OR. Visualization
methods
provide augmented reality viewing of the patient, exposing hidden
structures to
the surgeon, as well as the locations of her instruments relative to
critical
structures. We will describe our experience in building and deploying
such
image guided surgical systems, and describe their impact on several
hundred
actual surgical procedures.
About the Speaker
Eric Grimson received a B.Sc. in Mathematics and Physics from
the University of Regina, and a Ph.D. in Mathematics from the
Massachusetts Institute of Technology. He is currently
Professor of Computer Science and Engineering and Associate Director
of the Artificial Intelligence Laboratory at MIT, a Lecturer on
Radiology at Harvard Medical School, and holds the Bernard Gordon
Chair of Medical Engineering at MIT.
His current research interests include: medical image
computation, image guided surgery, activity detection and
classification in
video, trainable vision systems, image database indexing, and object
recognition.
Contact: bac-coordinators@cs.stanford.edu
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