title: Postoperative 3D spine reconstruction by navigating partitioning manifolds.
abstract: OBJECTIVE
  The postoperative evaluation of scoliosis patients undergoing corrective treatment is an important task to assess the strategy of the spinal surgery. Using accurate 3D geometric models of the patient's spine is essential to measure longitudinal changes in the patient's anatomy. On the other hand, reconstructing the spine in 3D from postoperative radiographs is a challenging problem due to the presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine.
  
  
  METHODS
  This paper describes the reconstruction problem by searching for the optimal model within a manifold space of articulated spines learned from a training dataset of pathological cases who underwent surgery. The manifold structure is implemented based on a multilevel manifold ensemble to structure the data, incorporating connections between nodes within a single manifold, in addition to connections between different multilevel manifolds, representing subregions with similar characteristics.
  
  
  RESULTS
  The reconstruction pipeline was evaluated on x-ray datasets from both preoperative patients and patients with spinal surgery. By comparing the method to ground-truth models, a 3D reconstruction accuracy of 2.24 ± 0.90 mm was obtained from 30 postoperative scoliotic patients, while handling patients with highly deformed spines.
  
  
  CONCLUSIONS
  This paper illustrates how this manifold model can accurately identify similar spine models by navigating in the low-dimensional space, as well as computing nonlinear charts within local neighborhoods of the embedded space during the testing phase. This technique allows postoperative follow-ups of spinal surgery using personalized 3D spine models and assess surgical strategies for spinal deformities.
authors.affiliation: Department of Computer and Software Engineering, Ecole Polytechnique Montreal, Montréal, Québec H3C 3A7, Canada.
authors.forename: Samuel
authors.initials: S
authors.lastname: Kadoury
authors.affiliation: CHU Sainte-Justine Hospital Research Center, Montréal, Québec H3T 1C5, Canada.
authors.forename: Hubert
authors.initials: H
authors.lastname: Labelle
authors.affiliation: CHU Sainte-Justine Hospital Research Center, Montréal, Québec H3T 1C5, Canada.
authors.forename: Stefan
authors.initials: S
authors.lastname: Parent
mesh_terms: D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D011184:Postoperative Period; D012044:Regression Analysis; D012600:Scoliosis / Q000000981:diagnostic imaging / Q000601:surgery; D013131:Spine / Q000000981:diagnostic imaging* / Q000601:surgery*; D014057:Tomography, X-Ray Computed