An inverse methodology for high-frequency RF coil design for MRI with de-emphasized B-1 fields

An inverse methodology for the design of biologically loaded radio-frequency (RF) coils for magnetic resonance imaging applications is described. Free space time-harmonic electromagnetic Green's functions and de-emphasized B-1 target fields are used to calculate the current density on the coil cylinder. In theory, with the B-1 field de-emphasized in the middle of the RF transverse plane, the calculated current distribution can generate an internal magnetic field that can reduce the central overemphasis effect caused by field/tissue interactions at high frequencies. The current distribution of a head coil operating at 4 T (170 MHz) is calculated using an inverse methodology with de-emphasized B-1. target fields. An in-house finite-difference time-domain routine is employed to evaluate B-1 field and signal intensity inside a homogenous cylindrical phantom and then a complete human head model. A comparison with a conventional RF birdcage coil is carried out and demonstrates that this method can help in decreasing the normal bright region caused by field/tissue interactions in head images at 170 MHz and higher field strengths.

An inverse methodology for high frequency RF head coil design with pre-emphasized B1 field in MRI

An inverse methodology to assist in the design of radio-frequency (RF) head coils for high field MRI application is described in this work. Free space time-harmonic electromagnetic Green's functions and preemphasized B1 field are used to calculate the current density on the coil cylinder. With B1 field preemphasized and lowered in the middle of the RF transverse plane, the calculated current distribution can generate an internal magnetic field that can reduce the EM field/tissue interactions at high frequencies. The current distribution of a head coil operating at 4 T is calculated using inverse methodology with preemphasized B1 fields. FDTD is employed to calculate B1 field and signal intensity inside a homogenous cylindrical phantom and human head. A comparison with conventional RF birdcage coil is reported here and demonstrated that inverse-method designed coil with preemphasized B1 field can help in decreasing the notorious bright region caused by EM field/tissue interactions in the human head images at 4 T.

A theoretical comparison of two optimization methods for radiofrequency drive schemes in high frequency MRI resonators

In this paper, numerical simulations are used in an attempt to find optimal Source profiles for high frequency radiofrequency (RF) volume coils. Biologically loaded, shielded/unshielded circular and elliptical birdcage coils operating at 170 MHz, 300 MHz and 470 MHz are modelled using the FDTD method for both 2D and 3D cases. Taking advantage of the fact that some aspects of the electromagnetic system are linear, two approaches have been proposed for the determination of the drives for individual elements in the RF resonator. The first method is an iterative optimization technique with a kernel for the evaluation of RF fields inside an imaging plane of a human head model using pre-characterized sensitivity profiles of the individual rungs of a resonator; the second method is a regularization-based technique. In the second approach, a sensitivity matrix is explicitly constructed and a regularization procedure is employed to solve the ill-posed problem. Test simulations show that both methods can improve the B-1-field homogeneity in both focused and non-focused scenarios. While the regularization-based method is more efficient, the first optimization method is more flexible as it can take into account other issues such as controlling SAR or reshaping the resonator structures. It is hoped that these schemes and their extensions will be useful for the determination of multi-element RF drives in a variety of applications.

An advanced regularization methodology for use in watershed model calibration

A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.

Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.