title: Automatic image-to-world registration based on x-ray projections in cone-beam CT-guided interventions.
abstract: Intraoperative imaging offers a means to account for morphological changes occurring during the procedure and resolve geometric uncertainties via integration with a surgical navigation system. Such integration requires registration of the image and world reference frames, conventionally a time consuming, error-prone manual process. This work presents a method of automatic image-to-world registration of intraoperative cone-beam computed tomography (CBCT) and an optical tracking system. Multimodality (MM) markers consisting of an infrared (IR) reflective sphere with a 2 mm tungsten sphere (BB) placed precisely at the center were designed to permit automatic detection in both the image and tracking (world) reference frames. Image localization is performed by intensity thresholding and pattern matching directly in 2D projections acquired in each CBCT scan, with 3D image coordinates computed using backprojection and accounting for C-arm geometric calibration. The IR tracking system localized MM markers in the world reference frame, and the image-to-world registration was computed by rigid point matching of image and tracker point sets. The accuracy and reproducibility of the automatic registration technique were compared to conventional (manual) registration using a variety of marker configurations suitable to neurosurgery (markers fixed to cranium) and head and neck surgery (markers suspended on a subcranial frame). The automatic technique exhibited subvoxel marker localization accuracy (< 0.8 mm) for all marker configurations. The fiducial registration error of the automatic technique was (0.35 +/-0.01) mm, compared to (0.64 +/- 0.07 mm) for the manual technique, indicating improved accuracy and reproducibility. The target registration error (TRE) averaged over all configurations was 1.14 mm for the automatic technique, compared to 1.29 mm for the manual in accuracy, although the difference was not statistically significant (p = 0.3). A statistically significant improvement in precision was observed-specifically, the standard deviation in TRE was 0.2 mm for the automatic technique versus 0.34 mm for the manual technique (p = 0.001). The projection-based automatic registration technique demonstrates accuracy and reproducibility equivalent or superior to the conventional manual technique for both neurosurgical and head and neck marker configurations. Use of this method with C-arm CBCT eliminates the burden of manual registration on surgical workflow by providing automatic registration of surgical tracking in 3D images within approximately 20 s of acquisition, with registration automatically updated with each CBCT scan. The automatic registration method is undergoing integration in ongoing clinical trials of intraoperative CBCT-guided head and neck surgery.
authors: Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 2M9, Canada.
authors: N M
authors: NM
authors: Hamming
authors: M J
authors: MJ
authors: Daly
authors: J C
authors: JC
authors: Irish
authors: J H
authors: JH
authors: Siewerdsen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D054893:Cone-Beam Computed Tomography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000295:instrumentation / Q000379:methods*