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RARE imaging: A fast imaging method for clinical MR
Abstract
Based on the principles of echo imaging, we presnet a method to acquire sufficient data for a 256 × 256 image in from 2 to 40s. The image contrast is dominated by the transverse relaxation time T2 Sampling all projections for 2D FT image reconstruction in one (or a few) echo trains leads to image artifacts due to the different T2 weighting of the echo. These artifacts cannot be described by a simple smearing out of the image in the phase direction. Proper distribution of the phase‐encoding steps on the echoes can be used to minimize artifacts and even lead to resolution enhancement. In spite of the short data acquisition times, the signal amplitudes of structures with long T2 are nearly the same as those in a conventional 2D FT experiment. Our method, therefore, is an ideal screening technique for lesions with long T2. © 1986 Academic Press, Inc.
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Citations
Cited by
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Knabl, J., Witschi, R., Hösl, K., Reinold, H., Zeilhofer, U. B., Ahmadi, S., Brockhaus, J., Sergejeva, M., Hess, A., Brune, K., et al. (2008) · Nature · doi:10.1038/nature06493 · Cited by 438
Zaitsev, M., Dold, C., Sakas, G., Hennig, J., & Speck, O. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.039 · Cited by 391
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Optimized Single-Slab Three-dimensional Spin-Echo MR Imaging of the Brain
Mugler, J. P., Bao, S., Mulkern, R. V., Guttmann, C. R. G., Robertson, R. L., Jolesz, F. A., & Brookeman, J. R. (2000) · Radiology · doi:10.1148/radiology.216.3.r00au46891 · Cited by 334
Metadata
- Authors
- Hennig, J., Nauerth, A., & Friedburg, H.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 1986-12
- Volume
- 3
- Issue
- 6
- Pages
- 823-833
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W2154108863
- Cited by
- 2,081
- References
- 0
- FWCI
- 5.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Hennig, J., Nauerth, A., & Friedburg, H. (1986). RARE imaging: A fast imaging method for clinical MR. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.1910030602
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
