<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>Recent techniques of radiofrequency (RF) probes and preamplifiers in Magnetic Resonance Imaging (MRI) developments almost reached the physical limits of signal to noise ratio (SNR). More improvements in speed accelerations of data acquisition are very difficult to achieve. One exception, called RF phased array coils, is recently being developed very progressively. The approach is conceptually similar to phased array used in radar techniques; hence it is usually called MRI phased array coils. It is necessary to ensure independence of the individual coil channels in the array by the coil and preamp decoupling and the coil geometry optimization to get maximum benefits from this technique. Thus, the qualitative design and method for optimization of geometric properties of the coil elements in phased arrays, with aim to increase SNR, minimize the G-factor and to limit noise correlation, are proposed in this paper. By the finite element method (FEM) simulations, we obtained the sensitivity maps and inductances of the coils. The introduced program primarily calculates the Sensitivity Encoding (SENSE) G-factor along with other parameters that can be derived from sensitivity maps. By the proposed optimization algorithm, the program is capable to calculate the optimal values of the geometric coil parameters in a relatively small number of iterations.</p></abstract>

Recent techniques of radiofrequency (RF) probes and preamplifiers in Magnetic Resonance Imaging (MRI) developments almost reached the physical limits of signal to noise ratio (SNR). More improvements in speed accelerations of data acquisition are very difficult to achieve. One exception, called RF phased array coils, is recently being developed very progressively. The approach is conceptually similar to phased array used in radar techniques; hence it is usually called MRI phased array coils. It is necessary to ensure independence of the individual coil channels in the array by the coil and preamp decoupling and the coil geometry optimization to get maximum benefits from this technique. Thus, the qualitative design and method for optimization of geometric properties of the coil elements in phased arrays, with aim to increase SNR, minimize the G-factor and to limit noise correlation, are proposed in this paper. By the finite element method (FEM) simulations, we obtained the sensitivity maps and inductances of the coils. The introduced program primarily calculates the Sensitivity Encoding (SENSE) G-factor along with other parameters that can be derived from sensitivity maps. By the proposed optimization algorithm, the program is capable to calculate the optimal values of the geometric coil parameters in a relatively small number of iterations.

Phased Array Receiving Coils for Low Field Lungs MRI: Design and Optimization

Institute of Measurement Science, Department of Imaging Methods, Slovak Academy of Sciences, Dúbravská cesta 9, 84104 Bratislava, Slovakia

Department of Radiology, Vienna General Hospital, Medical University of Vienna, Waeringer Guertel 18-20, A-1090, Vienna, Austria

Measurement Science Review

{"article-title":"Phased Array Receiving Coils for Low Field Lungs MRI: Design and Optimization"}

Recent techniques of radiofrequency (RF) probes and preamplifiers in Magnetic Resonance Imaging (MRI) developments almost reached the physical limits of signal...

Phased Array Receiving Coils for Low Field Lungs MRI: Design and Optimization

Publicado en línea: 03 jun 2011

Páginas: 61 - 66

DOI: https://doi.org/10.2478/v10048-011-0012-3

Palabras clave
magnetic resonance imaging, phased array, field calculation, optimization

This content is open access.

Phased Array Receiving Coils for Low Field Lungs MRI: Design and Optimization

Publicado en línea: 03 jun 2011

Páginas: 61 - 66

DOI: https://doi.org/10.2478/v10048-011-0012-3

Palabras clavemagnetic resonance imaging, phased array, field calculation, optimization

This content is open access.

Palabras clave
magnetic resonance imaging, phased array, field calculation, optimization