Types: Doctoral thesis
Subjects: info:eu-repo/classification/ddc/530, MRI, Rapid relaxation time mapping, Rapid motion estimation, Magnetic resonance imaging
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.
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