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21 May 1999Effect of vertebral surface extraction on registration accuracy: a comparison of registration results for iso-intensity algorithms applied to computed tomography images
This paper presents a comparison of iso-intensity-based surface extraction algorithms applied to computed tomography (CT) images of the spine. The extracted vertebral surfaces are used in surface-based registration of CT images to physical space, where our ultimate goal is the development of a technique that can be used for image-guided spinal surgery. The surface extraction process has a direct effect on image-guided surgery in two ways: the extracted surface must provide an accurate representation of the actual surface so that a good registration can be achieved, and the number of polygons in the mesh representation of the extracted surface must be small enough to allow the registration to be performed quickly. To examine the effect of the surface extraction process on registration error and run time, we have performed a large number of experiments on two plastic spine phantoms. Using a marker-based system to assess accuracy, we have found that submillimetric registration accuracy can be achieved using a point-to- surface registration algorithm with simplified and unsimplified members of the general class of iso-intensity- based surface extraction algorithms. This research has practical implications, since it shows that several versions of the widely available class of intensity-based surface extraction algorithms can be used to provide sufficient accuracy for vertebral registration. Since intensity-based algorithms are completely deterministic and fully automatic, this finding simplifies the pre-processing required for image-guided back surgery.
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Jeannette L. Herring, Calvin R. Maurer Jr., Diane M. Muratore, Robert L. Galloway Jr., Benoit M. Dawant, "Effect of vertebral surface extraction on registration accuracy: a comparison of registration results for iso-intensity algorithms applied to computed tomography images," Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348488