Conference proceeding
CT-video registration accuracy for virtual guidance of bronchoscopy
Proceedings of SPIE, Vol.5369(1), pp.150-164
Medical Imaging 2004: Physiology, Function, and Structure from Medical Images
04/30/2004
DOI: 10.1117/12.534125
Abstract
Bronchoscopic biopsy is often used for assisting the assessment of lung cancer. We have found in previous research that live image guidance of bronchoscopy has much potential for improving biopsy outcome. We have devised a system for this purpose. During a guided bronchoscopy procedure, our system simultaneously draws upon both the bronchoscope's video stream and the patient's 3D MDCT volume. The key data-processing step during guided bronchoscopy is the registration of the 3D MDCT data volume to the bronchoscopic video. The registration process is initialized by assuming that the bronchoscope is at a fixed viewpoint, giving a target reference video image, while the virtual-world camera inside the MDCT volume begins at an initial viewpoint that is within a reasonable vicinity of the bronchoscope's viewpoint. During registration, an optimization process searches for the optimal viewpoint to give the virtual image best matching the fixed video target. Overall, we have found that the CT-video registration technique operates robustly over a wide range of conditions, with considerable flexibility in the initial-viewpoint choice. Further, the system appears to be largely insensitive to the differences in lung capacity during the MDCT scan and during bronchoscopy. Finally, the system matches effectively in a wide range of anatomical circumstances.
Details
- Title: Subtitle
- CT-video registration accuracy for virtual guidance of bronchoscopy
- Creators
- James P Helferty - Pennsylvania State UniversityEric A Hoffman - University of IowaGeoffrey McLennan - University of IowaWilliam E Higgins - Pennsylvania State University
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.5369(1), pp.150-164
- Conference
- Medical Imaging 2004: Physiology, Function, and Structure from Medical Images
- DOI
- 10.1117/12.534125
- ISSN
- 0277-786X
- Language
- English
- Date published
- 04/30/2004
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
- Record Identifier
- 9984318815702771
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