Deformable 3D-2D registration of known components for image guidance in spine surgery
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 9902 LNCS, Page: 124-132
2016
- 17Citations
- 21Captures
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Metrics Details
- Citations17
- Citation Indexes17
- 17
- CrossRef9
- Captures21
- Readers21
- 21
Conference Paper Description
A 3D-2D image registration method is reported for guiding the placement of surgical devices (e.g.,K-wires). The solution registers preoperative CT (and planning data therein) to intraoperative radiographs and computes the pose,shape,and deformation parameters of devices (termed “components”) known to be in the radiographic scene. The deformable known-component registration (dKC-Reg) method was applied in experiments emulating spine surgery to register devices (K-wires and spinal fixation rods) undergoing realistic deformation. A two-stage registration process (i) resolves patient pose from individual radiographs and (ii) registers components represented as polygonal meshes based on a B-spline model. The registration result can be visualized as overlay of the component in CT analogous to surgical navigation but without conventional trackers or fiducials. Target registration error in the tip and orientation of deformable K-wires was (1.5 ± 0.9) mm and (0.6° ± 0.2°),respectively. For spinal fixation rods,the registered components achieved Hausdorff distance of 3.4 mm. Future work includes testing in cadaver and clinical data and extension to more generalized deformation and component models.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84996590137&origin=inward; http://dx.doi.org/10.1007/978-3-319-46726-9_15; http://www.ncbi.nlm.nih.gov/pubmed/37195053; https://link.springer.com/10.1007/978-3-319-46726-9_15; https://dx.doi.org/10.1007/978-3-319-46726-9_15; https://link.springer.com/chapter/10.1007/978-3-319-46726-9_15
Springer Science and Business Media LLC
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