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Neonatal brain and cardiac imaging would benefit from the increased signal-to-noise ratio levels at 7 T compared to lower field. Optimal performance might be achieved using purpose designed RF coil arrays. In this study, we introduce an 8-channel dipole array and investigate, using simulations, its RF performances for neonatal applications at 7 T.
MethodsThe 8-channel dipole array was designed and evaluated for neonatal brain/cardiac configurations in terms of SAR efficiency (ratio between transmit-field and maximum specific-absorption-rate level) using adjusted dielectric properties for neonate. A birdcage coil operating in circularly polarized mode was simulated for comparison. Validation of the simulation model was performed on phantom for the coil array.
ResultsThe 8-channel dipole array demonstrated up to 46% higher SAR efficiency levels compared to the birdcage coil in neonatal configurations, as the specific-absorption-rate levels were alleviated. An averaged normalized root-mean-square-error of 6.7% was found between measured and simulated transmit field maps on phantom.
ConclusionThe 8-channel dipole array design integrated for neonatal brain and cardiac MR was successfully demonstrated, in simulation with coverage of the baby and increased SAR efficiency levels compared to the birdcage. We conclude that the 8Tx-dipole array promises safe operating procedures for MR imaging of neonatal brain and heart at 7 T.
相似文献In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.
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