Vol 49, No 2 (2018)

The data of magnetic resonance imaging (MRI) studies include not only grayscale images, but also textual information associated with them —personal data about the patient, parameters of scanning and data processing, etc. This information is stored separately from graphic images. Therefore, the possibility for its correction and loss cannot be excluded. In this paper, the method of generation of marker information on diagnostic images is described. The marker information, as a textual analogue, is entered on the image during an MRI scan and becomes an integral part of the diagnostic material along with the images of anatomical structures. The method is realized by using the selective radiofrequency presaturation of non-scanable slices oriented perpendicularly to the scanned slices. It leads to the formation of bands of reduced signal in the areas of intersections of these slices on images. In this case, the band thicknesses are equal to the thicknesses of non-scanable slices. Different combinations of these bands (marker lines) are formed directly on images and can contain information about MRI studies. This information is determined not only by positions and angle orientations of bands, but also by their thickness, total brightness and brightness distribution in the transverse direction of these bands. The examples of introducing and positioning the marker information in conventional MRI studies are presented.

Parallel magnetic resonance imaging (MRI) (pMRI) uses multiple receiver coils to reduce the MRI scan time. To accelerate the data acquisition process in MRI, less amount of data is acquired from the scanner which leads to artifacts in the reconstructed images. SENSitivity Encoding (SENSE) is a reconstruction algorithm in pMRI to remove aliasing artifacts from the undersampled multi coil data and recovers fully sampled images. The main limitation of SENSE is computing inverse of the encoding matrix. This work proposes the inversion of encoding matrix using Jacobi singular value decomposition (SVD) algorithm for image reconstruction on GPUs to accelerate the reconstruction process. The performance of Jacobi SVD is compared with Gauss–Jordan algorithm. The simulations are performed on two datasets (brain and cardiac) with acceleration factors 2, 4, 6 and 8. The results show that the graphics processing unit (GPU) provides a speed up to 21.6 times as compared to CPU reconstruction. Jacobi SVD algorithm performs better in terms of acceleration in reconstructions on GPUs as compared to Gauss–Jordan method. The proposed algorithm is suitable for any number of coils and acceleration factors for SENSE reconstruction on real time processing systems.

Copper foil has been widely employed in conventional radio frequency (RF) birdcage coils for magnetic resonance imaging (MRI). However, for ultrahigh-field (UHF) MRI, current density distribution on the copper foil is concentrated on the surface and the edge due to proximity effect. This increases the effective resistance and distorts the circumferential sinusoidal current distribution on the birdcage coils, resulting in low signal-to-noise ratio (SNR) and inhomogeneous distribution of RF magnetic (B₁) field. In this context, multiple parallel round wires were proposed as legs of a birdcage coil to optimize current density distribution and to improve the SNR and the B₁ field homogeneity. The design was compared with three conventional birdcage coils with different width flat strip surface legs for a 9.4 T (T) MRI system, e.g., narrow-leg birdcage coil (NL), medium-leg birdcage coil (ML), broad-leg birdcage coil (BL) and the multiple parallel round wire-leg birdcage coil (WL). Studies were carried out in in vitro saline phantom as well as in vivo mouse brain. WL showed higher coil quality factor Q and more homogeneous B₁ field distribution compared to the other three conventional birdcage coils. Furthermore, WL showed 12, 10 and 13% SNR increase, respectively, compared to NL, ML and BL. It was proposed that conductor’s shape optimization could be an effective approach to improve RF coil performance for UHF MRI.