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The temperature of the gradient coils is an important issue in the development of MRI scanners. Gradient coil performance must be maximised within temperature limits imposed by safety and system requirements. Here we present a model that determines the temperature distribution in gradient coils designed using an inverse boundary element method (IBEM). This forward approach is derived by applying a constant boundary element method (BEM) on a steady-state approximation of the heat equation and combined with the stream function associated to an electric current density. It can be used to estimate the temperature distribution, as well as, the location and temperature of hot spots in gradient coils of arbitrary shape. Several examples of the applicability of the proposed BEM model on different coil geometries and thermal characteristics are presented. In order to validate the method, a small prototype X -gradient coil was built and tested, and the temperature distribution experimentally measured. It was found to be in a good agreement to the temperature distribution simulated by the proposed numerical approach with a suitable choice of the thermal properties. [ABSTRACT FROM AUTHOR]

Highlights: [•] Our main goal is to perform six degrees of freedom pose registration in semi-structured environments. [•] We use two cameras, Kinect and SR4000, and compare them in order to determine accuracy. [•] We also compare two basic methods, ICP and Ransac. [•] We propose the use of a Growing Neural Gas to represent fast and high quality 3D spaces. [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation is a promising tool in neuroscience of which successful development is affected by the loud click noise originated when the stimulating coil is energized. This undesired sound is produced by the coil winding deformations generated by the Lorentz self-forces in the TMS device. Addressing the need for TMS systems that produce less noise, a quiet coil design technique is proposed in this work, where instead of minimizing directly the coil deflection, the Lorentz self-force is optimized in order to reduce the acoustic noise. The presented method is based on a stream function IBEM for TMS coil design in which new computational models have been incorporated into the optimization problem, which is efficiently solved by using supporting vector analysis. Several examples of coils of different geometries were designed and simulated to demonstrate the efficiency of the suggested IBEM approach to produce TMS devices that experience minimum Lorentz self-forces. In order to evaluate the acoustic response of the designed TMS coils, the commercial MSC/NASTRAN was used to find the coil deflection. The obtained results show that significant noise reduction can be achieved by minimizing the Lorentz self-force over the TMS coil surface. [ABSTRACT FROM AUTHOR]

An inverse boundary element method and efficient optimisation techniques were combined to produce a versatile framework to design optimal TMS coils. The presented approach can be seen as an improvement and extension of the work introduced by Cobos Sanchez et al. [1] where the optimality of the resulting coil solutions was not guaranteed. This new numerical framework based on a constant boundary element method has been efficiently applied to produce optimal TMS coils with arbitrary geometry, allowing the inclusion of new coil features in the design process, such as optimised maximum current density or reduced temperature. Even the structural properties of the human head were considered using this approach at the design stage to produce more realistic TMS stimulators. Several examples of TMS coils were designed and simulated to demonstrate the validity of the proposed boundary element method approach, and the obtained results show that the described method is an efficient tool for the design of optimal TMS stimulators, which can be applied to a wide range of coil geometries and performance requirements considering the natural variability in the human head properties. [ABSTRACT FROM AUTHOR]