The DOI matches its Crossref record.
Self‐calibrating parallel imaging with automatic coil sensitivity extraction
Open accessAbstract
Calibration of the spatial sensitivity functions of coil arrays is a crucial element in parallel magnetic resonance imaging (PMRI). The most common approach has been to measure coil sensitivities directly using one or more low‐resolution images acquired before or after accelerated data acquisition. However, since it is difficult to ensure that the patient and coil array will be in exactly the same positions during both calibration scans and accelerated imaging, this approach can introduce sensitivity miscalibration errors into PMRI reconstructions. This work shows that it is possible to extract sensitivity calibration images directly from a fully sampled central region of a variable‐density k‐space acquisition. These images have all the features of traditional PMRI sensitivity calibrations and therefore may be used for any PMRI reconstruction technique without modification. Because these calibration data are acquired simultaneously with the data to be reconstructed, errors due to sensitivity miscalibration are eliminated. In vivo implementations of self‐calibrating parallel imaging using a flexible coil array are demonstrated in abdominal imaging and in real‐time cardiac imaging studies. Magn Reson Med 47:529–538, 2002. © 2002 Wiley‐Liss, Inc.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Zaitsev, M., Hennig, J., & Speck, O. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20261 · Cited by 349
Optimized 3D ultrashort echo time pulmonary MRI
Johnson, K. M., Fain, S. B., Schiebler, M. L., & Nagle, S. (2013) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24570 · Cited by 322
Linear inverse problems in imaging
Ribes, A., & Schmitt, F. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2008.923099 · Cited by 154
Metadata
- Authors
- McKenzie, C. A., Yeh, E. N., Ohliger, M. A., Price, M. D., & Sodickson, D. K.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2002-02-20
- Volume
- 47
- Issue
- 3
- Pages
- 529-538
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W1991732515
- Cited by
- 189
- References
- 0
- FWCI
- 8.58
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Self‐calibrating parallel imaging with automatic coil sensitivity extraction. https://app.cochat.ai/papers/10.1002/mrm.10087
- The paper
- McKenzie, C. A., Yeh, E. N., Ohliger, M. A., Price, M. D., & Sodickson, D. K. (2002). Self‐calibrating parallel imaging with automatic coil sensitivity extraction. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.10087
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.