title: Joint surface reconstruction and 4D deformation estimation from sparse data and prior knowledge for marker-less Respiratory motion tracking.
abstract: OBJECTIVE
  The intraprocedural tracking of respiratory motion has the potential to substantially improve image-guided diagnosis and interventions. The authors have developed a sparse-to-dense registration approach that is capable of recovering the patient's external 3D body surface and estimating a 4D (3D + time) surface motion field from sparse sampling data and patient-specific prior shape knowledge.
  
  
  METHODS
  The system utilizes an emerging marker-less and laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3D measurements in real-time. These sparse position measurements are registered with a dense reference surface extracted from planning data. Thereby a dense displacement field is recovered, which describes the spatio-temporal 4D deformation of the complete patient body surface, depending on the type and state of respiration. It yields both a reconstruction of the instantaneous patient shape and a high-dimensional respiratory surrogate for respiratory motion tracking. The method is validated on a 4D CT respiration phantom and evaluated on both real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured-light scanner.
  
  
  RESULTS
  In the experiments, the authors estimated surface motion fields with the proposed algorithm on 256 datasets from 16 subjects and in different respiration states, achieving a mean surface reconstruction accuracy of ± 0.23 mm with respect to ground truth data-down from a mean initial surface mismatch of 5.66 mm. The 95th percentile of the local residual mesh-to-mesh distance after registration did not exceed 1.17 mm for any subject. On average, the total runtime of our proof of concept CPU implementation is 2.3 s per frame, outperforming related work substantially.
  
  
  CONCLUSIONS
  In external beam radiation therapy, the approach holds potential for patient monitoring during treatment using the reconstructed surface, and for motion-compensated dose delivery using the estimated 4D surface motion field in combination with external-internal correlation models.
authors.affiliation: Institute for Numerical Simulation, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115 Bonn, Germany. benjamin.berkels@ins.unibonn.de
authors.forename: Benjamin
authors.initials: B
authors.lastname: Berkels
authors.forename: Sebastian
authors.initials: S
authors.lastname: Bauer
authors.forename: Svenja
authors.initials: S
authors.lastname: Ettl
authors.forename: Oliver
authors.initials: O
authors.lastname: Arold
authors.forename: Joachim
authors.initials: J
authors.lastname: Hornegger
authors.forename: Martin
authors.initials: M
authors.lastname: Rumpf
mesh_terms: D005260:Female; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D009068:Movement; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012119:Respiration