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The finite-difference time-domain (FDTD) method is used to model a birdcage resonator. All the coil components, including the wires, lumped capacitors and the source, are geometrically modelled together. As such, the coupling effects within the birdcage, including the interactions of coil, source and human head, are accurately computed. A study of the transverse magnetic (B1) field homogeneity and the specific absorption rate (SAR) is presented on an anatomically detailed human head model at 64 and 200 MHz representing 1.5 and 4.7 T MRI systems respectively. Unlike that at 64 MHz, the B1 field distribution is found to be inhomogeneous at 200 MHz. Also, high local SAR values are observed in the tissue near the source due to the coupling between the source and the head at 200 MHz.

Theoretical results demonstrate that distilled water can sustain dielectric resonances in head-sized spheres near 200 and 360 MHz, but the presence of significant conductivity suppresses these resonances. These findings are confirmed experimentally with proton images of water and saline (0.05 and 0.125 M NaCl). For lossy phantoms, coupling between the source and phantom overwhelms the dielectric resonance. Because of their low relative permittivity, mineral oil phantoms with 20 cm diameter do not exhibit dielectric resonances below approximately 900 MHz. Significant dielectric resonances were not observed in human head images obtained at 1.5, 4.7, and 8 T.

AbstractÐWe present and compare methods for feature-level (predetection) and decision-level (postdetection) fusion of multisensor data. This study emphasizes fusion techniques that are suitable for noncommensurate data sampled at noncoincident points. Decision-level fusion is most convenient for such data, but it is suboptimal in principle, since targets not detected by all sensors will not obtain the full benefits of fusion. A novel algorithm for feature-level fusion of noncommensurate, noncoincidently sampled data is described, in which a model is fitted to the sensor data and the model parameters are used as features. Formulations for both featurelevel and decision-level fusion are described, along with some practical simplifications. A closed-form expression is available for feature-level fusion of normally distributed data and this expression is used with simulated data to study requirements for sample position accuracy in multisensor data. The performance of feature-level and decision-level fusion algorithms are compared for experimental data acquired by a metal detector, a ground-penetrating radar, and an infrared camera at a challenging test site containing surrogate mines. It is found that fusion of binary decisions does not perform significantly better than the best available sensor. The performance of feature-level fusion is significantly better than the individual sensors, as is decision-level fusion when detection confidence information is also available (ªsoft-decisionº fusion).

In this work, the B1 field homogeneity and specific absorption rate (SAR) values were evaluated for three high-frequency (340 MHz) radio frequency coils designed for use in human magnetic resonance imaging at 8 tesla. Eight-, 16-, and 24-strut transverse electromagnetic (TEM) resonators were examined both experimentally and with the finite difference time domain numerical method. It was observed that increasing the number of TEM elements acted to lower the maximal achievable frequency of the coil and to increase the experimental complexities associated with tuning and matching. In addition, it is demonstrated from experiment and numerical analysis that the circularly polarized component of the B1 (B1+) field homogeneity in the head improved most from 8- to 16-strut coils. Numerical analysis revealed little difference in terms of SAR distribution between these coils; however, stronger tissue/coil coupling and consequently higher SAR peak values were obtained for the 8-strut case.