Paper
12 April 2005 Automated skull tracking for the CyberKnife image-guided radiosurgery system
Dongshan Fu, Gopinath Kuduvalli, Vladimir Mitrovic, William Main, Larry Thomson
Author Affiliations +
Abstract
We have developed an automated skull tracking method to perform near real-time patient alignment and position correction during CyberKnife image-guided intracranial radiosurgery. Digitally reconstructed radiographs (DRRs) are first generated offline from a CT study before treatment, and are used as reference images for the patient position. Two orthogonal projection X-ray images are then acquired at the time of patient alignment or treatment. Multi-phase registration is used to register the DRRs with the X-ray images. The registration in each projection is carried out independently; the results are then combined and converted to a 3-D rigid transformation. The in-plane transformation and the out-of-plane rotations are estimated using different search methods including multi-resolution matching, steepest descent minimization and one-dimensional search. Two similarity measure methods, optimized pattern intensity and sum of squared difference (SSD), are applied at different search phases to optimize both accuracy and computation speed. Experiments on an anthropomorphic skull phantom showed that the tracking accuracy (RMS error) is better than 0.3 mm for each translation and better than 0.3 degree for each rotation, and the targeting accuracy (clinically relevant accuracy) tested with the CyberKnife system is better than 1 mm. The computation time required for the tracking algorithm is within a few seconds.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dongshan Fu, Gopinath Kuduvalli, Vladimir Mitrovic, William Main, and Larry Thomson "Automated skull tracking for the CyberKnife image-guided radiosurgery system", Proc. SPIE 5744, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display, (12 April 2005); https://doi.org/10.1117/12.594984
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CITATIONS
Cited by 14 scholarly publications and 4 patents.
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KEYWORDS
Image registration

X-rays

X-ray imaging

Head

X-ray computed tomography

Detection and tracking algorithms

Skull

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