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Optimal control theory for applications in Magnetic Resonance Imaging
- Source :
- Pacific Journal of Mathematics for Industry, Vol 9, Iss 1, Pp 1-10 (2017), Pacific Journal of Mathematics for Industry, Pacific Journal of Mathematics for Industry, 2017, 9 (1), pp.54103-54103. 〈10.1186/s40736-017-0034-3〉, Pacific Journal of Mathematics for Industry, Springer, 2017, 9 (1), pp.54103-54103. ⟨10.1186/s40736-017-0034-3⟩, Pacific Journal of Mathematics for Industry, 2017, 9 (1), pp.54103-54103. ⟨10.1186/s40736-017-0034-3⟩
- Publication Year :
- 2017
- Publisher :
- SpringerOpen, 2017.
-
Abstract
- We apply innovative mathematical tools coming from optimal control theory to improve theoretical and experimental techniques in Magnetic Resonance Imaging (MRI). This approach allows us to explore and to experimentally reach the physical limits of the corresponding spin dynamics in the presence of typical experimental imperfections and limitations. We study in this paper two important goals, namely the optimization of image contrast and the maximization of the signal to noise per unit time. We anticipate that the proposed techniques will find practical applications in medical imaging in a near future to help the medical diagnosis.<br />Comment: 19 pages, 7 figures, to be published in Pacific Journal of Mathematics for Industry
- Subjects :
- Quantum Physics
[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging
Magnetic resonance imaging
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
Optimal control theory
lcsh:T57-57.97
lcsh:Applied mathematics. Quantitative methods
FOS: Physical sciences
Spin dynamics
Quantum Physics (quant-ph)
[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging
Subjects
Details
- Language :
- English
- ISSN :
- 21984115
- Volume :
- 9
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Pacific Journal of Mathematics for Industry
- Accession number :
- edsair.doi.dedup.....2c3d68f66479a461aee62d89b4645e14