
Proceedings Paper
Localizing and tracking electrodes using stereovision in epilepsy casesFormat | Member Price | Non-Member Price |
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Paper Abstract
In epilepsy cases, subdural electrodes are often implanted to acquire intracranial EEG (iEEG) for seizure localization and
resection planning. However, the electrodes may shift significantly between implantation and resection, during the time
that the patient is monitored for iEEG recording. As a result, the accuracy of surgical planning based on electrode
locations at the time of resection can be compromised. Previous studies have only quantified the electrode shift with
respect to the skull, but not with respect to the cortical surface, because tracking cortical shift between surgeries is
challenging. In this study, we use an intraoperative stereovision (iSV) system to visualize and localize the cortical
surface as well as electrodes, record three-dimensional (3D) locations of the electrodes in MR space at the time of
implantation and resection, respectively, and quantify the raw displacements, i.e., with respect to the skull. Furthermore,
we track the cortical surface and quantify the shift between surgeries using an optical flow (OF) based motion-tracking
algorithm. Finally, we compute the electrode shift with respect to the cortical surface by subtracting the cortical shift
from raw measured displacements. We illustrate the method using one patient example. In this particular patient case, the
results show that the electrodes not only shifted significantly with respect to the skull (8.79 ± 3.00 mm in the lateral
direction, ranging from 2.88 mm to 12.87 mm), but also with respect to the cortical surface (7.20 ± 3.58 mm), whereas
the cortical surface did not shift significantly in the lateral direction between surgeries (2.23 ± 0.76 mm).
Paper Details
Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94150G (18 March 2015); doi: 10.1117/12.2082016
Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)
PDF: 8 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94150G (18 March 2015); doi: 10.1117/12.2082016
Show Author Affiliations
Xiaoyao Fan, Thayer School of Engineering at Dartmouth (United States)
Songbai Ji, Thayer School of Engineering at Dartmouth (United States)
Geisel School of Medicine (United States)
Songbai Ji, Thayer School of Engineering at Dartmouth (United States)
Geisel School of Medicine (United States)
David W. Roberts, Geisel School of Medicine (United States)
Norris Cotton Cancer Ctr. (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Keith D. Paulsen, Thayer School of Engineering at Dartmouth (United States)
Geisel School of Medicine (United States)
Norris Cotton Cancer Ctr. and Dartmouth-Hitchcock Medical Ctr. (United States)
Norris Cotton Cancer Ctr. (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Keith D. Paulsen, Thayer School of Engineering at Dartmouth (United States)
Geisel School of Medicine (United States)
Norris Cotton Cancer Ctr. and Dartmouth-Hitchcock Medical Ctr. (United States)
Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)
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