Biomechanically constrained groupwise US to CT registration of the lumbar spine.

Sean Gill, Parvin Mousavi, Gabor Fichtinger, Elvis Chen, Jonathan Boisvert, David Pichora, Purang Abolmaesumi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Registration of intraoperative ultrasound (US) with preoperative computed tomography (CT) data for interventional guidance is a subject of immense interest, particularly for percutaneous spinal injections. We propose a biomechanically constrained group-wise registration of US to CT images of the lumbar spine. Each vertebra in CT is treated as a sub-volume and transformed individually. The sub-volumes are then reconstructed into a single volume. The algorithm simulates an US image from the CT data at each iteration of the registration. This simulated US image is used to calculate an intensity based similarity metric with the real US image. A biomechanical model is used to constrain the displacement of the vertebrae relative to one another. Covariance Matrix Adaption - Evolution Strategy (CMA-ES) is utilized as the optimization strategy. Validation is performed on CT and US images from a phantom designed to preserve realistic curvatures of the spine. The technique is able to register initial misalignments of up to 20 mm with a success rate of 82%, and those of up to 10 mm with a success rate of 98.6%.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages803-810
Number of pages8
Volume12
EditionPt 1
StatePublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)

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