The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Image Similarity and Tissue Overlaps as Surrogates for Image Registration Accuracy: Widely Used but Unreliable
Open accessAbstract
The accuracy of nonrigid image registrations is commonly approximated using surrogate measures such as tissue label overlap scores, image similarity, image difference, or transformation inverse consistency error. This paper provides experimental evidence that these measures, even when used in combination, cannot distinguish accurate from inaccurate registrations. To this end, we introduce a "registration" algorithm that generates highly inaccurate image transformations, yet performs extremely well in terms of the surrogate measures. Of the tested criteria, only overlap scores of localized anatomical regions reliably distinguish reasonable from inaccurate registrations, whereas image similarity and tissue overlap do not. We conclude that tissue overlap and image similarity, whether used alone or together, do not provide valid evidence for accurate registrations and should thus not be reported or accepted as such.
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Cites
Nonrigid registration using free-form deformations: application to breast mr images
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Multimodality image registration by maximization of mutual information
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Image matching as a diffusion process: an analogy with maxwell’s demons
Thirion, J.-P. (1998) · Medical Image Analysis · doi:10.1016/s1361-8415(98)80022-4 · Cited by 2,445
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration
Klein, A., Andersson, J., Ardekani, B. A., Ashburner, J., Avants, B., Chiang, M.-C., Christensen, G. E., Collins, D. L., Gee, J., Hellier, P., et al. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.037 · Cited by 2,227
Birkfellner, W., Stock, M., Figl, M., Gendrin, C., Hummel, J., Dong, S., Kettenbach, J., Georg, D., & Bergmann, H. (2009) · Medical Physics · doi:10.1118/1.3157111 · Cited by 44
Cited by
Deformable medical image registration: a survey
Sotiras, A., Davatzikos, C., & Paragios, N. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2265603 · Cited by 1,587
“…for image registration ( i.e. , Non-rigid Image Regis-tration Evaluation Project - NIREP [450]) and the increasing understanding regarding the use of surrogate measures for the measurement of the accuracy of registration [451] will further facilitate the comparison between different algorithms.”
BackgroundDeep MRI brain extraction: A 3D convolutional neural network for skull stripping
Kleesiek, J., Urban, G., Hubert, A., Schwarz, D., Maier-Hein, K., Bendszus, M., & Biller, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.024 · Cited by 505
A Hierarchical Fused Fuzzy Deep Neural Network for Data Classification
Deng, Y., Ren, Z., Kong, Y., Bao, F., & Dai, Q. (2017) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2016.2574915 · Cited by 396
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
Guha Roy, A., Conjeti, S., Navab, N., & Wachinger, C. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.042 · Cited by 267
A survey of methods for 3D histology reconstruction
Pichat, J., Iglesias, J. E., Yousry, T., Ourselin, S., & Modat, M. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.02.004 · Cited by 207
Metadata
- Authors
- Rohlfing, T.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2012-02
- Volume
- 31
- Issue
- 2
- Pages
- 153-163
- ISSN
- 0278-0062 (ISSN-L)
- 1558-254X
- OpenAlex
- W2054902886
- Cited by
- 412
- References
- 5
- FWCI
- 16.91
- Type
- journal article
- Language
- en
- Open access
- green
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- Rohlfing, T. (2012). Image Similarity and Tissue Overlaps as Surrogates for Image Registration Accuracy: Widely Used but Unreliable. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/tmi.2011.2163944
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