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@ARTICLE{Maximov:189741,
      author       = {Maximov, Ivan I. and Vinding, Mads S. and Tse, Desmond H.
                      Y. and Nielsen, Niels Chr. and Shah, N. J.},
      title        = {{R}eal-time 2{D} spatially selective {MRI} experiments:
                      {C}omparative analysis of optimal control design methods},
      journal      = {Journal of magnetic resonance},
      volume       = {254},
      issn         = {1090-7807},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2015-02773},
      pages        = {110 - 120},
      year         = {2015},
      abstract     = {There is an increasing need for development of advanced
                      radio-frequency (RF) pulse techniques in modern magnetic
                      resonance imaging (MRI) systems driven by recent
                      advancements in ultra-high magnetic field systems, new
                      parallel transmit/receive coil designs, and accessible
                      powerful computational facilities. 2D spatially selective RF
                      pulses are an example of advanced pulses that have many
                      applications of clinical relevance, e.g., reduced field of
                      view imaging, and MR spectroscopy.The 2D spatially selective
                      RF pulses are mostly generated and optimised with numerical
                      methods that can handle vast controls and multiple
                      constraints. With this study we aim at demonstrating that
                      numerical, optimal control (OC) algorithms are efficient for
                      the design of 2D spatially selective MRI experiments, when
                      robustness towards e.g. field inhomogeneity is in focus. We
                      have chosen three popular OC algorithms; two which are
                      gradient-based, concurrent methods using first- and
                      second-order derivatives, respectively; and a third that
                      belongs to the sequential, monotonically convergent family.
                      We used two experimental models: a water phantom, and an in
                      vivo human head. Taking into consideration the challenging
                      experimental setup, our analysis suggests the use of the
                      sequential, monotonic approach and the second-order
                      gradient-based approach as computational speed, experimental
                      robustness, and image quality is key. All algorithms used in
                      this work were implemented in the MATLAB environment and are
                      freely available to the MRI community.},
      cin          = {INM-4 / JARA-BRAIN},
      ddc          = {550},
      cid          = {I:(DE-Juel1)INM-4-20090406 / $I:(DE-82)080010_20140620$},
      pnm          = {573 - Neuroimaging (POF3-573)},
      pid          = {G:(DE-HGF)POF3-573},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000355071100015},
      doi          = {10.1016/j.jmr.2015.03.003},
      url          = {https://juser.fz-juelich.de/record/189741},
}