Retrospective intermodality registration techniques for images of the head: surface-based versus volume-based

Abstract

The primary objective of this study is to perform a blinded evaluation of two groups of retrospective image registration techniques, using as a gold standard a prospective marker-based registration method, and to compare the performance of one group with the other. These techniques have already been evaluated individually [27]. In this paper, however, we find that by grouping the techniques as volume based or surface based, we can make some interesting conclusions which were not visible in the earlier study. In order to ensure blindness, all retrospective registrations were performed by participants who had no knowledge of the gold-standard results until after their results had been submitted. Image volumes of three modalities: X-ray computed tomography (CT), magnetic resonance (MR), and positron emission tomography (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 (VOI's). Our results indicate that the volume-based techniques in this study tended to give substantially more accurate and reliable results than the surface-based ones for the CT-to-MR registration tasks, and slightly more accurate results for the PET-to-MR tasks. Analysis of these results revealed that the rotational component of error was more pronounced for the surface-based group. It was also apparent that all of the registration techniques we examined have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.

The Superiority of Tsallis Entropy over Traditional Cost Functions for Brain MRI and SPECT Registration

“…In comparative studies [44,45], as many as 16 retrospective registration methods from 12 research groups worldwide were evaluated with respect to the MIS and NMI performance in rigid multimodal brain images registration. Ground truth was obtained using bone-implanted skull markers [46].…”

Brain Functional Localization: A Survey of Image Registration Techniques

“…Based on FRE measures in the RREP framework, West et al [140] compared the performance of eight surface-based (feature-based) and six volume-based (intensity-based) registration techniques and concluded that the volume-based techniques were significantly more accurate than surface-based techniques in CT to anatomic MRI registration and were also slightly more accurate in PET to anatomic MRI registration. In the same study, they also performed a statistical hypothesis test on the differences between the results obtained from MR images corrected and uncorrected for field inhomogeneity, and did not find the difference significant for PET to anatomic MRI registration.…”

Rigid Registration of Medical Images Using 1D and 2D Binary Projections

“…Surface-based techniques rely on the characteristics of the surface of the registrable objects while volume-based techniques use the full volume information. West et al [3] define as volume-based "any technique which performs registration by making use of a relationship between voxel intensities within the images and as surface-based, any technique which works by minimizing a distance measure between two corresponding surfaces in the images to be matched". According to Slomka et al [2] volume-or voxel-based techniques are more robust and accurate because they do not rely on the preprocessing of the images for being accurate.…”

“…The methods may be suitable for image-to-image space registration (3D-3D, 2D-3D) or physical to image space registration. 3D-3D methods register image volumes to image volumes (MR-MR, CT-MR, (positron emission tomography) PET-MR, Ultrasound-MR) [2,3,10]. 2D-3D registration techniques register, for example, one or more intraoperative X-ray projections of the patient and the preoperative 3D volume [11,12].…”