Intensity-based 2D-3D spine image registration incorporating a single fiducial marker.
OBJECTIVE
The two-dimensional (2D)-three dimensional (3D) registration of a computed tomography image to one or more x-ray projection images has a number of image-guided therapy applications. In general, fiducial marker-based methods are fast, accurate, and robust, but marker implantation is not always possible, often is considered too invasive to be clinically acceptable, and entails risk. There also is the unresolved issue of whether it is acceptable to leave markers permanently implanted. Intensity-based registration methods do not require the use of markers and can be automated because such geometric features as points and surfaces do not need to be segmented from the images. However, for spine images, intensity-based methods are susceptible to local optima in the cost function and thus need initial transformations that are close to the correct transformation.


METHODS
In this report, we propose a hybrid similarity measure for 2D-3D registration that is a weighted combination of an intensity-based similarity measure (mutual information) and a point-based measure using one fiducial marker. We evaluate its registration accuracy and robustness by using gold-standard clinical spine image data from four patients.


RESULTS
Mean registration errors for successful registrations for the four patients were 1.3 and 1.1 mm for the intensity-based and hybrid similarity measures, respectively. Whereas the percentage of successful intensity-based registrations (registration error < 2.5 mm) decreased rapidly as the initial transformation got further from the correct transformation, the incorporation of a single marker produced successful registrations more than 99% of the time independent of the initial transformation.


CONCLUSIONS
The use of one fiducial marker reduces 2D-3D spine image registration error slightly and improves robustness substantially. The findings are potentially relevant for image-guided therapy. If one marker is sufficient to obtain clinically acceptable registration accuracy and robustness, as the preliminary results using the proposed hybrid similarity measure suggest, the marker can be placed on a spinous process, which could be accomplished without penetrating muscle or using fluoroscopic guidance, and such a marker could be removed relatively easily.
Russakoff
Daniel B
DB
Department of Computer Science, Stanford University, 300 Pasteur Drive, Stanford, CA 94305-5327, USA.
Rohlfing
Torsten
T
Adler
John R
JR
Maurer
Calvin R
CR
D000465:Algorithms; D002138:Calibration; D002574:Cervical Vertebrae / Q000000981:diagnostic imaging; D004867:Equipment Design; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016634:Radiosurgery / Q000295:instrumentation / Q000379:methods; D013122:Spinal Diseases / Q000601:surgery; D013131:Spine / Q000000981:diagnostic imaging; D025321:Surgery, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D013904:Thoracic Vertebrae / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*