The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
State of the Art: Iterative CT Reconstruction Techniques
Open accessAbstract
Owing to recent advances in computing power, iterative reconstruction (IR) algorithms have become a clinically viable option in computed tomographic (CT) imaging. Substantial evidence is accumulating about the advantages of IR algorithms over established analytical methods, such as filtered back projection. IR improves image quality through cyclic image processing. Although all available solutions share the common mechanism of artifact reduction and/or potential for radiation dose savings, chiefly due to image noise suppression, the magnitude of these effects depends on the specific IR algorithm. In the first section of this contribution, the technical bases of IR are briefly reviewed and the currently available algorithms released by the major CT manufacturers are described. In the second part, the current status of their clinical implementation is surveyed. Regardless of the applied IR algorithm, the available evidence attests to the substantial potential of IR algorithms for overcoming traditional limitations in CT imaging.
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Cites
Mathews, J. D., Forsythe, A. V., Brady, Z., Butler, M. W., Goergen, S. K., Byrnes, G. B., Giles, G. G., Wallace, A. B., Anderson, P. R., Guiver, T. A., et al. (2013) · BMJ · doi:10.1136/bmj.f2360 · Cited by 2,029
Cited by
Wang, G. (2016) · IEEE Access · doi:10.1109/access.2016.2624938 · Cited by 455
Shan, H., Padole, A., Homayounieh, F., Kruger, U., Khera, R. D., Nitiwarangkul, C., Kalra, M. K., & Wang, G. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0057-9 · Cited by 417
Greffier, J., Hamard, A., Pereira, F., Barrau, C., Pasquier, H., Beregi, J. P., & Frandon, J. (2020) · European Radiology · doi:10.1007/s00330-020-06724-w · Cited by 328
Militello, C., Rundo, L., Toia, P., Conti, V., Russo, G., Filorizzo, C., Maffei, E., Cademartiri, F., La Grutta, L., Midiri, M., et al. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.103424 · Cited by 71
Metadata
- Authors
- Geyer, L. L., Schoepf, U. J., Meinel, F. G., Nance, J. W., Bastarrika, G., Leipsic, J. A., Paul, N. S., Rengo, M., Laghi, A., & De Cecco, C. N.
- Venue
- Radiology
- Published
- 2015-08
- Volume
- 276
- Issue
- 2
- Pages
- 339-357
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W1949839429
- Cited by
- 704
- References
- 1
- FWCI
- 32.52
- Type
- journal article
- Language
- en
- Open access
- green
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- Geyer, L. L., Schoepf, U. J., Meinel, F. G., Nance, J. W., Bastarrika, G., Leipsic, J. A., Paul, N. S., Rengo, M., Laghi, A., & De Cecco, C. N. (2015). State of the Art: Iterative CT Reconstruction Techniques. Radiology. https://doi.org/10.1148/radiol.2015132766
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