title: Geometric-feature-based spectral graph matching in pharyngeal surface registration.
abstract: Fusion between an endoscopic movie and a CT can aid specifying the tumor target volume for radiotherapy. That requires a deformable pharyngeal surface registration between a 3D endoscope reconstruction and a CT segmentation. In this paper, we propose to use local geometric features for deriving a set of initial correspondences between two surfaces, with which an association graph can be constructed for registration by spectral graph matching. We also define a new similarity measurement to provide a meaningful way for computing inter-surface affinities in the association graph. Our registration method can deal with large non-rigid anatomical deformation, as well as missing data and topology change. We tested the robustness of our method with synthetic deformations and showed registration results on real data.
authors.forename: Qingyu
authors.initials: Q
authors.lastname: Zhao
authors.forename: Stephen
authors.initials: S
authors.lastname: Pizer
authors.forename: Marc
authors.initials: M
authors.lastname: Niethammer
authors.forename: Julian
authors.initials: J
authors.lastname: Rosenman
mesh_terms: D000465:Algorithms; D004724:Endoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D064847:Multimodal Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010610:Pharyngeal Neoplasms / Q000175:diagnosis*; D010614:Pharynx / Q000000981:diagnostic imaging / Q000473:pathology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*