Jay West, J. Michael Fitzpatrick, Matthew Y. Wang, Benoit M. Dawant, Calvin R. Maurer, Robert M. Kessler, Robert J. Maciunas, Christian Barillot, Didier Lemoine, André Collignon, Frederik Maes, Paul Suetens, Dirk Vandermeulen, Petra A. van den Elsen, Sandy Napel, Thilaka S. Sumanaweera, Beth Harkness, Paul F. Hemler, Derek L. G. Hill, David J. Hawkes, Colin Studholme, J. B. Antoine Maintz, Max A. Viergever, Gregoire Malandain, Xavier Pennec, Marilyn E. Noz, Gerald Q. Maguire, Michael Pollack, Charles A. Pelizzari, Richard A. Robb, Dennis Hanson, Roger P. Woods, Department of Computer Science [Nashville], Vanderbilt University [Nashville], Department of Electrical Engineering & Computer Science [Nashville], Vision spatio-temporelle et active (VISTA), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Université de /Rennes, Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Wake Forest School of Medicine [Winston-Salem], Wake Forest Baptist Medical Center, Guy's and St Thomas' Hospital [London], University Medical Center [Utrecht], Medical imaging and robotics (EPIDAURE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), New York University Langone Medical Center (NYU Langone Medical Center), NYU System (NYU), The University of Chicago Medicine [Chicago], Mayo Clinic [Rochester], School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Université de Rennes, University of California-University of California, Loew, Murray H, and Hanson, Kenneth M
PURPOSE: The primary objective of this study is to perform a blinded evaluation of a group of retrospective image registration techniques using as a gold standard a prospective, marker-based registration method. To ensure blindedness, all retrospective registrations were performed by participants who had no knowledge of the gold standard results until after their results had been submitted. A secondary goal of the project is to evaluate the importance of correcting geometrical distortion in MR images by comparing the retrospective registration error in the rectified images, i.e., those that have had the distortion correction applied, with that of the same images before rectification. METHOD: Image volumes of three modalities (CT, MR, and PET) were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/ or from PET to MR. These investigators communicated their transformations again via the Internet to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOIs), i.e., areas in the brain that would commonly be areas of neurological interest. A VOI is defined in the MR image and its centroid c is determined. Then, the prospective registration is used to obtain the corresponding point c' in CT or PET. To this point, the retrospective registration is then applied, producing c" in MR. Statistics are gathered on the target registration error (TRE), which is the distance between the original point c and its corresponding point c". RESULTS: This article presents statistics on the TRE calculated for each registration technique in this study and provides a brief description of each technique and an estimate of both preparation and execution time needed to perform the registration. CONCLUSION: Our results indicate that retrospective techniques have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors. Journal of computer assisted tomography, vol. 21, no. 4, pp. 554-566, 1997, Lippincott-Raven Publishers, Philadelphia, PA, USA (1997 Giovanni DiChiro Award for Outstanding Scientific Research published in the Journal of Computer Assisted Tomography) ispartof: Journal of computer assisted tomography vol:21 issue:4 pages:554-566 ispartof: location:CA, NEWPORT BEACH status: published