Biomechanically constrained groupwise ultrasound to CT registration of the lumbar spine

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DOIResolve DOI: http://doi.org/10.1016/j.media.2010.07.008
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TypeArticle
Journal titleMedical Image Analysis
ISSN13618415
Volume16
Issue3
Pages662674
SubjectUltrasound; Spine; Multimodal registration; Biomechanical model
AbstractWe present a groupwise US to CT registration algorithm for guiding percutaneous spinal interventions. In addition, we introduce a comprehensive validation scheme that accounts for changes in the curvature of the spine between preoperative and intraoperative imaging. In our registration methodology, each vertebra in CT is treated as a sub-volume and transformed individually. A biomechanical model is used to constrain the displacement of the vertebrae relative to one another. The sub-volumes are then reconstructed into a single volume. During each iteration of registration, an US image is simulated from the reconstructed CT volume and an intensity-based similarity metric is calculated with the real US image. Validation studies are performed on CT and US images from a sheep cadaver, five patient-based phantoms designed to preserve realistic curvatures of the spine and a sixth patient-based phantom where the curvature of the spine is changed between preoperative and intraoperative imaging. For datasets where the spine curve between two imaging modalities was artificially perturbed, the proposed methodology was able to register initial misalignments of up to 20 mm with a success rate of 95%. For the phantom with a physical change in the curvature of the spine introduced between the US and CT datasets, the registration success rate was 98.5%. Finally, the registration success rate for the sheep cadaver with soft-tissue information was 87%. The results demonstrate that our algorithm allows for robust registration of US and CT datasets, regardless of a change in the patients pose between preoperative and intraoperative image acquisitions.
Publication date
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
IdentifierS1361841510001003
NPARC number21268816
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Record identifier1b0b6d6a-6968-400d-9e6a-f44bb21b3b57
Record created2013-11-14
Record modified2016-05-09
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