A comparison of similarity measures for use in 2-D-3-D medical image registration
Abstract
A comparison of six similarity measures for use in intensity-based two-dimensional-three-dimensional (2-D-3-D) image registration is presented. The accuracy of the similarity measures are compared to a "gold-standard" registration which has been accurately calculated using fiducial markers. The similarity measures are used to register a computed tomography (CT) scan of a spine phantom to a fluoroscopy image of the phantom. The registration is carried out within a region-of-interest in the fluoroscopy image which is user defined to contain a single vertebra. Many of the problems involved in this type of registration are caused by features which were not modeled by a phantom image alone. More realistic "gold-standard" data sets were simulated using the phantom image with clinical image features overlaid. Results show that the introduction of soft-tissue structures and interventional instruments into the phantom image can have a large effect on the performance of some similarity measures previously applied to 2-D-3-D image registration. Two measures were able to register accurately and robustly even when soft-tissue structures and interventional instruments were present as differences between the images. These measures were pattern intensity and gradient difference. Their registration accuracy, for all the rigid-body parameters except for the source to film translation, was within a root-mean-square (rms) error of 0.54 mm or degrees to the "gold-standard" values. No failures occ…
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GI and GC metrics have been shown previously to be useful when handling partial content mismatch.
“The GI and GC metrics have been shown previously (Penney et al 1998, Pluim et al 2000, Otake et al 2012b) to be useful when handling partial content mismatch.”
From 3D–2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch (2016) · cites this paper as Penney et al 1998
Image gradients can filter out low spatial frequency differences such as soft tissue and act as a high-pass filter to focus registration on bony anatomy visible in x-ray images.
“Image gradients can be used to filter out low spatial frequency differences such as soft tissue (Penney et al 1998, Pluim et al 2000) and act as a high-pass filter to focus the registration on the bony anatomy clearly visible in x-ray images.”
From 3D–2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch (2016) · cites this paper as Penney et al 1998
Gradient-based metrics have shown promise in 3D-2D image registration problems involving intraoperative radiographs and preoperative CT images.
“From the similarity metrics that have been previously investigated, gradient-based metrics have shown promise in 3D–2D image registration problems involving intraoperative radiographs and preoperative CT images (Penney et al 1998, Gendrin et al 2011, Otake et al 2012b, 2015).”
From 3D–2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch (2016) · cites this paper as Penney et al 1998
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- Authors
- Penney, G. P., Weese, J., Little, J. A., Desmedt, P., Hill, D. L. G., & hawkes, D. J.
- Affiliations
- Guy's Hospital (GB)
- Philips (Germany) (DE)
- Philips (Netherlands) (NL)
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 1998
- Volume
- 17
- Issue
- 4
- Pages
- 586-595
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2134042740
- Cited by
- 782
- References
- 1
- Citations by year
- 2026: 7 · 2025: 15 · 2024: 12 · 2023: 19 · 2022: 15 · 2021: 19 · 2020: 13 · 2019: 10 · 2018: 22 · 2017: 23 · 2016: 31 · 2015: 32 · 2014: 41 · 2013: 45 · 2012: 43
- FWCI
- 16.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Medical Imaging (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Physics and Astronomy › Radiation › Advanced Radiotherapy Techniques
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Keywords
- similarity measures, intensity-based registration, fluoroscopy, computed tomography, spine phantom, soft tissue structures, gradient difference, rigid registration, registration accuracy
- MeSH terms
- Algorithms, Fluoroscopy, Humans, Spine, Tomography, X-Ray Computed, Phantoms, Imaging
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