Abstract
We present a system for registering the coordinate frame of an endoscope to pre- or intra-operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.
| Original language | English (US) |
|---|---|
| Title of host publication | Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling |
| Publisher | SPIE |
| Volume | 9415 |
| ISBN (Print) | 9781628415056 |
| DOIs | |
| State | Published - 2015 |
| Event | Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling - Orlando, United States Duration: Feb 22 2015 → Feb 24 2015 |
Other
| Other | Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling |
|---|---|
| Country | United States |
| City | Orlando |
| Period | 2/22/15 → 2/24/15 |
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Keywords
- Endoscopic sinus surgery
- Image-guided endoscopic surgery
- Rendering-based video-CT registration
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Radiology Nuclear Medicine and imaging
Cite this
Rendering-based video-CT registration with physical constraints for image-guided endoscopic sinus surgery. / Otake, Y.; Leonard, S.; Reiter, A.; Rajan, P.; Siewerdsen, Jeff; Ishii, Masaru; Taylor, Russell H; Hager, Gregory.
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling. Vol. 9415 SPIE, 2015. 94150A.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Rendering-based video-CT registration with physical constraints for image-guided endoscopic sinus surgery
AU - Otake, Y.
AU - Leonard, S.
AU - Reiter, A.
AU - Rajan, P.
AU - Siewerdsen, Jeff
AU - Ishii, Masaru
AU - Taylor, Russell H
AU - Hager, Gregory
PY - 2015
Y1 - 2015
N2 - We present a system for registering the coordinate frame of an endoscope to pre- or intra-operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.
AB - We present a system for registering the coordinate frame of an endoscope to pre- or intra-operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.
KW - Endoscopic sinus surgery
KW - Image-guided endoscopic surgery
KW - Rendering-based video-CT registration
UR - http://www.scopus.com/inward/record.url?scp=84943546968&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84943546968&partnerID=8YFLogxK
U2 - 10.1117/12.2081732
DO - 10.1117/12.2081732
M3 - Conference contribution
C2 - 25991876
AN - SCOPUS:84943546968
SN - 9781628415056
VL - 9415
BT - Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
PB - SPIE
ER -