| Popis: |
Recent technological developments in the field of magnetic resonance imaging have resulted in advanced techniques that can reduce the total time to acquire images. For applications such as relaxation time mapping, which enables improved visualisation of in vivo structures, rapid imaging techniques are highly desirable. TAPIR is a Look- Locker-based sequence for high-resolution, multislice T1 relaxation time mapping. Despite the high accuracy and precision of TAPIR, an improvement in the k-space sampling trajectory is desired to acquire data in clinically acceptable times. In this thesis, a new trajectory, termed line-sharing, is introduced for TAPIR that can potentially reduce the acquisition time by 40 %. Additionally, the line-sharing method was compared with the GRAPPA parallel imaging method. These methods were employed to reconstruct time-point images from the data acquired on a 4T high-field MR research scanner. Multislice, multipoint in vivo results obtained using these methods are presented. Despite improvement in acquisition speed, through line-sharing, for example, motion remains a problem and artefact-free data cannot always be obtained. Therefore, in this thesis, a rapid technique is introduced to estimate in-plane motion. The presented technique is based on calculating the in-plane motion parameters, i.e., translation and rotation, by registering the low-resolution MR images. The rotation estimation method is based on the pseudo-polar FFT, where the Fourier domain is composed of frequencies that reside in an oversampled set of non-angularly, equispaced points. The essence of the method is that unlike other Fourier-based registration schemes, the employed approach does not require any interpolation to calculate the pseudo-polar FFT grid coordinates. Translation parameters are estimated by the phase correlation method. However, instead of two-dimensional analysis of the phase correlation matrix, a low complexity subspace identification of the phase correlation matrix is employed. This method is beneficial because it offers sub-pixel displacement estimation without interpolation, increased robustness to noise and limited computational complexity. Owing to all these advantages, the proposed technique is very suitable for the real-time implementation to solve the motion correction problem. |
