Literature DB >> 12906184

Incorporation of a laser range scanner into image-guided liver surgery: surface acquisition, registration, and tracking.

David M Cash1, Tuhin K Sinha, William C Chapman, Hiromi Terawaki, Benoit M Dawant, Robert L Galloway, Michael I Miga.   

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.

Mesh:

Year:  2003        PMID: 12906184      PMCID: PMC4445740          DOI: 10.1118/1.1578911

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  25 in total

1.  Surgically induced intracranial contrast enhancement: potential source of diagnostic error in intraoperative MR imaging.

Authors:  M Knauth; N Aras; C R Wirtz; A Dörfler; T Engelhorn; K Sartor
Journal:  AJNR Am J Neuroradiol       Date:  1999-09       Impact factor: 3.825

2.  SonoWand, an ultrasound-based neuronavigation system.

Authors:  A Gronningsaeter; A Kleven; S Ommedal; T E Aarseth; T Lie; F Lindseth; T Langø; G Unsgård
Journal:  Neurosurgery       Date:  2000-12       Impact factor: 4.654

3.  Intraoperative ultrasound for guidance and tissue shift correction in image-guided neurosurgery.

Authors:  R M Comeau; A F Sadikot; A Fenster; T M Peters
Journal:  Med Phys       Date:  2000-04       Impact factor: 4.071

4.  Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model.

Authors:  M Ferrant; A Nabavi; B Macq; F A Jolesz; R Kikinis; S K Warfield
Journal:  IEEE Trans Med Imaging       Date:  2001-12       Impact factor: 10.048

5.  Fast finite elements for surgery simulation.

Authors:  M Bro-Nielsen
Journal:  Stud Health Technol Inform       Date:  1997

6.  Laser triangulation: fundamental uncertainty in distance measurement.

Authors:  R G Dorsch; G Häusler; J M Herrmann
Journal:  Appl Opt       Date:  1994-03-01       Impact factor: 1.980

7.  Image-guided neurosurgery with intraoperative MRI: update of frameless stereotaxy and radicality control.

Authors:  C R Wirtz; V M Tronnier; M M Bonsanto; M Knauth; A Staubert; F K Albert; S Kunze
Journal:  Stereotact Funct Neurosurg       Date:  1997       Impact factor: 1.875

8.  Constitutive modelling of brain tissue: experiment and theory.

Authors:  K Miller; K Chinzei
Journal:  J Biomech       Date:  1997 Nov-Dec       Impact factor: 2.712

9.  Intraoperative magnetic resonance imaging to update interactive navigation in neurosurgery: method and preliminary experience.

Authors:  C R Wirtz; M M Bonsanto; M Knauth; V M Tronnier; F K Albert; A Staubert; S Kunze
Journal:  Comput Aided Surg       Date:  1997

10.  Intraoperative magnetic resonance imaging combined with neuronavigation: a new concept.

Authors:  C Nimsky; O Ganslandt; H Kober; M Buchfelder; R Fahlbusch
Journal:  Neurosurgery       Date:  2001-05       Impact factor: 4.654

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  22 in total

1.  Design and evaluation of an optically-tracked single-CCD laser range scanner.

Authors:  Thomas S Pheiffer; Amber L Simpson; Brian Lennon; Reid C Thompson; Michael I Miga
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

2.  A clinically applicable laser-based image-guided system for laparoscopic liver procedures.

Authors:  Matteo Fusaglia; Hanspeter Hess; Marius Schwalbe; Matthias Peterhans; Pascale Tinguely; Stefan Weber; Huanxiang Lu
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-10-17       Impact factor: 2.924

3.  A method to track cortical surface deformations using a laser range scanner.

Authors:  Tuhin K Sinha; Benoit M Dawant; Valerie Duay; David M Cash; Robert J Weil; Reid C Thompson; Kyle D Weaver; Michael I Miga
Journal:  IEEE Trans Med Imaging       Date:  2005-06       Impact factor: 10.048

4.  Concepts and preliminary data toward the realization of image-guided liver surgery.

Authors:  David M Cash; Michael I Miga; Sean C Glasgow; Benoit M Dawant; Logan W Clements; Zhujiang Cao; Robert L Galloway; William C Chapman
Journal:  J Gastrointest Surg       Date:  2007-07       Impact factor: 3.452

5.  Robust surface registration using salient anatomical features for image-guided liver surgery: algorithm and validation.

Authors:  Logan W Clements; William C Chapman; Benoit M Dawant; Robert L Galloway; Michael I Miga
Journal:  Med Phys       Date:  2008-06       Impact factor: 4.071

6.  Feasibility study for image-guided kidney surgery: assessment of required intraoperative surface for accurate physical to image space registrations.

Authors:  Anne B Benincasa; Logan W Clements; S Duke Herrell; Robert L Galloway
Journal:  Med Phys       Date:  2008-09       Impact factor: 4.071

7.  Registration of 3D shapes under anisotropic scaling: Anisotropic-scaled iterative closest point algorithm.

Authors:  Elvis C S Chen; A Jonathan McLeod; John S H Baxter; Terry M Peters
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-04-11       Impact factor: 2.924

8.  Generalized iterative most likely oriented-point (G-IMLOP) registration.

Authors:  Seth Billings; Russell Taylor
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-05-23       Impact factor: 2.924

9.  A novel method for texture-mapping conoscopic surfaces for minimally invasive image-guided kidney surgery.

Authors:  Rowena Ong; Courtenay L Glisson; Jessica Burgner-Kahrs; Amber Simpson; Andrei Danilchenko; Ray Lathrop; S Duke Herrell; Robert J Webster; Michael Miga; Robert L Galloway
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-01-13       Impact factor: 2.924

10.  Near Real-Time Computer Assisted Surgery for Brain Shift Correction Using Biomechanical Models.

Authors:  Kay Sun; Thomas S Pheiffer; Amber L Simpson; Jared A Weis; Reid C Thompson; Michael I Miga
Journal:  IEEE J Transl Eng Health Med       Date:  2014-04-30       Impact factor: 3.316

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