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Signal Modeling and the Cramér-Rao Bound for Absolute Magnetic Resonance Thermometry in Fat Tissue
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. (Biomedical Systems)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. (Biomedical Systems)
2011 (English)In: Proc. 45th Asilomar Conference on Signals, Systems, and Computers, 2011, 80-84 p.Conference paper, Published paper (Refereed)
Abstract [en]

Magnetic Resonance Imaging of tissues with both fat and water resonances allows for absolute temperature mapping through parametric modeling. The fat resonance is used as a reference to determine the absolute water resonance frequency which is linearly related to the temperature. The goal of thispaper is to assess whether or not resonance frequency based absolute temperature mapping is feasible in fat tissue. This is done by examining identifiability conditions and analyzing the obtainable performance in terms of the Cramér-Rao Bound of the temperature estimates. We develop the model by including multiple fat peaks, since even small fat resonances can be significant compared to the small water component in fat tissue. It is showed that a high signal to noise ratio is needed for practical use on a 1.5 T scanner, and that higher field strengths can improve the bound significantly. It is also shown that the choice of sampling interval is important to avoid aliasing. In sum, this type of magnetic resonance thermometry is feasible for fat tissuein applications where high field strength is used or when high signal to noise ratio can be obtained.

Place, publisher, year, edition, pages
2011. 80-84 p.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-163132DOI: 10.1109/ACSSC.2011.6189959OAI: oai:DiVA.org:uu-163132DiVA: diva2:462821
Conference
45th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 6-9, 2011
Funder
EU, European Research Council, 247035
Available from: 2011-12-08 Created: 2011-12-08 Last updated: 2012-11-08Bibliographically approved

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Björk, MarcusBerglund, JohanKullberg, JoelStoica, Peter

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