title: Incorporation of a laser range scanner into image-guided liver surgery: surface acquisition, registration, and tracking.
abstract: As image guided surgical procedures become increasingly diverse, there will be more scenarios where point-based fiducials cannot be accurately localized for registration and rigid body assumptions no longer hold. As a result, procedures will rely more frequently on anatomical surfaces for the basis of image alignment and will require intraoperative geometric data to measure and compensate for tissue deformation in the organ. In this paper we outline methods for which a laser range scanner may be used to accomplish these tasks intraoperatively. A laser range scanner based on the optical principle of triangulation acquires a dense set of three-dimensional point data in a very rapid, noncontact fashion. Phantom studies were performed to test the ability to link range scan data with traditional modes of image-guided surgery data through localization, registration, and tracking in physical space. The experiments demonstrate that the scanner is capable of localizing point-based fiducials to within 0.2 mm and capable of achieving point and surface based registrations with target registration error of less than 2.0 mm. Tracking points in physical space with the range scanning system yields an error of 1.4 +/- 0.8 mm. Surface deformation studies were performed with the range scanner in order to determine if this device was capable of acquiring enough information for compensation algorithms. In the surface deformation studies, the range scanner was able to detect changes in surface shape due to deformation comparable to those detected by tomographic image studies. Use of the range scanner has been approved for clinical trials, and an initial intraoperative range scan experiment is presented. In all of these studies, the primary source of error in range scan data is deterministically related to the position and orientation of the surface within the scanner's field of view. However, this systematic error can be corrected, allowing the range scanner to provide a rapid, robust method of acquiring anatomical surfaces intraoperatively.
authors.affiliation: Department of Biomedical Engineering, Vanderbilt University, Box 351631, Station B, Nashville, Tennessee 37235, USA. dave.cash@vanderbilt.edu
authors.forename: David M
authors.initials: DM
authors.lastname: Cash
authors.forename: Tuhin K
authors.initials: TK
authors.lastname: Sinha
authors.forename: William C
authors.initials: WC
authors.lastname: Chapman
authors.forename: Hiromi
authors.initials: H
authors.lastname: Terawaki
authors.forename: Benoit M
authors.initials: BM
authors.lastname: Dawant
authors.forename: Robert L
authors.initials: RL
authors.lastname: Galloway
authors.forename: Michael I
authors.initials: MI
authors.lastname: Miga
mesh_terms: D000368:Aged; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007834:Lasers; D008099:Liver / Q000473:pathology* / Q000601:surgery*; D008113:Liver Neoplasms / Q000473:pathology / Q000601:surgery; D019047:Phantoms, Imaging; D010780:Photogrammetry / Q000379:methods*; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*