title: Marker-less reconstruction of dense 4-D surface motion fields using active laser triangulation for respiratory motion management.
abstract: To manage respiratory motion in image-guided interventions a novel sparse-to-dense registration approach is presented. We apply an emerging laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3-D 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 reconstructed which describes the 4-D deformation of the complete patient body surface and recovers a multi-dimensional respiratory signal for application in respiratory motion management. The method is validated on real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured light scanner. In a study on 16 subjects, the proposed algorithm achieved a mean reconstruction accuracy of +/- 0.22 mm w.r.t. ground truth data.
authors.affiliation: Pattern Recognition Lab, Dept. of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. sebastian.bauer@cs.fau.de
authors.forename: Sebastian
authors.initials: S
authors.lastname: Bauer
authors.forename: Benjamin
authors.initials: B
authors.lastname: Berkels
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: D000465:Algorithms; D003198:Computer Simulation; D003952:Diagnostic Imaging / Q000379:methods; D020342:Finite Element Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D007834:Lasers; D015233:Models, Statistical; D008962:Models, Theoretical; D009038:Motion; D019047:Phantoms, Imaging; D012119:Respiration