The DOI matches its Crossref record.
Versatile frequency domain fitting using time domain models and prior knowledge
Abstract
An iterative nonlinear least‐squares fitting algorithm in the frequency domain using time domain models for quantification of complex frequency domain MR spectra is presented. The algorithm allows incorporation of prior knowledge and has both the advantage of time‐domain fitting with respect to handling the problem of missing data points and truncated data sets and of frequency‐domain fitting with respect to multiple frequency‐selective fitting. The described algorithm can handle, in addition to Lorentzian and Gaussian line‐shapes, Voigt and nonanalytic lineshapes. The program allows the user the design of his own fitting strategy to optimize the probability of reaching the global least‐squares minimum. The application of the fitting program is illustrated with examples from in vivo 1 H– 31 P‐, and 13 C‐MR spectroscopy.
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
Pietz, J., Kreis, R., Rupp, A., Mayatepek, E., Rating, D., Boesch, C., & Bremer, H. J. (1999) · Journal of Clinical Investigation · doi:10.1172/jci5017 · Cited by 300
Self-citationItem, F., Heinzer-Schweizer, S., Wyss, M., Fontana, P., Lehmann, R., Henning, A., Weber, M., Boesiger, P., Boutellier, U., & Toigo, M. (2011) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00747.2010 · Cited by 22
Metadata
- Authors
- Slotboom, J., Boesch, C., & Kreis, R.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 1998-06
- Volume
- 39
- Issue
- 6
- Pages
- 899-911
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W2036379925
- Cited by
- 167
- References
- 0
- FWCI
- 9.45
- Type
- journal article
- Language
- en
- Open access
- closed
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: Versatile frequency domain fitting using time domain models and prior knowledge. https://app.cochat.ai/papers/10.1002/mrm.1910390607
- The paper
- Slotboom, J., Boesch, C., & Kreis, R. (1998). Versatile frequency domain fitting using time domain models and prior knowledge. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.1910390607
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.