The PRESTO sequence is a well-known 3-D fMRI imaging sequence. In this sequence the echo planar imaging technique is merged with the echo-shift technique. This combination results in a very fast image acquisition, which is required for fMRI examinations of neural activation in the human brain. The aim of this work was to use the basic Cartesian PRESTO sequence as a framework when developing a novel trajectory using a non-Cartesian grid. Our new pulse sequence, PRESTO CAN, rotates the k-space profiles around the ky-axis in a non-Cartesian manner. This results in a high sampling density close to the centre of the k-space, and at the same time it provides sparser data collection of the part of the k-space that contains less useful information. This "can- or cylinder-like" pattern is expected to result in a much faster k-space acquisition without loosing important spatial information. A new reconstruction algorithm was also developed. The purpose was to be able to construct an image volume from data obtained using the novel PRESTO CAN sequence. This reconstruction algorithm was based on the gridding technique, and a Kaiser-Bessel window was also used in order to re-sample the data onto a Cartesian grid. This was required to make 3-D Fourier transformation possible. In addition, simulations were also performed in order to verify the function of the reconstruction algorithm. Furthermore, in vitro tests showed that the development of the PRESTO CAN sequence and the corresponding reconstruction algorithm were highly successful. In the future, the results can relatively easily be extended and generalized for in vivo investigations. In addition, there are numerous exciting possibilities for extending the basic techniques described in this thesis.

When patients move during an MRI examination, severe artifacts arise in the reconstructed image and motion correction is therefore often desired. An in-plane motion correction algorithm suitable for PRESTO-CAN, a new 3D functional MRI method where sampling of k-space is radial in kx-direction and kz-direction and Cartesian in ky-direction, was implemented in this thesis work. Rotation and translation movements can be estimated and corrected for sepa- rately since the magnitude of the data is only affected by the rotation. The data were sampled in a radial pattern and the rotation was estimated by finding the translation in angular direction using circular correlation. Correlation was also used when finding the translation in x-direction and z-direction. The motion correction algorithm was evaluated on computer simulated data, the motion was detected and corrected for, and this resulted in images with greatly reduced artifacts due to patient movements. / När patienter rör sig under en MRI-undersökning uppstår artefakter i den rekonstruerande bilden och därför är det önskvärt med rörelsekorrigering. En 2D- rörelsekorrigeringsalgoritm som är anpassad för PRESTO-CAN har tagits fram. PRESTO-CAN är en ny fMRI-metod för 3D där samplingen av k-rummet är radiell i (kx,kz)-planet och kartesisk i ky-riktningen. Rotations- och translationsrörelser kan estimeras separat då magnituden av signalen bara påverkas av rotationsrörelser. Eftersom data är samplat radiellt kan rotationen estimeras genom att hitta translationen i vinkelled med hjälp av cirkulär korrelation. Korrelation används även för att hitta translationen i i x- och z-riktningen. Test på simulerat data visar att rörelsekorrigeringsalgoritmen både detekterar och korrigerar för rörelser vilket leder till bilder med mycket mindre rörelseartefakter.

MRI (Magnetic Resonance Imaging) is a medical imaging method that uses magnetic fields in order to retrieve images of the human body. This thesis revolves around a novel acquisition method of 3D fMRI (functional Magnetic Resonance Imaging) called PRESTO-CAN that uses a radial pattern in order to sample the (kx,kz)-plane of k-space (the frequency domain), and a Cartesian sample pattern in the ky-direction. The radial sample pattern allows for a denser sampling of the central parts of k-space, which contain the most basic frequency information about the structure of the recorded object. This allows for higher temporal resolution to be achieved compared with other sampling methods since a fewer amount of total samples are needed in order to retrieve enough information about how the object has changed over time. Since fMRI is mainly used for monitoring blood flow in the brain, increased temporal resolution means that we can be able to track fast changes in brain activity more efficiently.The temporal resolution can be further improved by reducing the time needed for scanning, which in turn can be achieved by applying parallel imaging. One such parallel imaging method is SENSE (SENSitivity Encoding). The scan time is reduced by decreasing the sampling density, which causes aliasing in the recorded images. The aliasing is removed by the SENSE method by utilizing the extra information provided by the fact that multiple receiver coils with differing sensitivities are used during the acquisition. By measuring the sensitivities of the respective receiver coils and solving an equation system with the aliased images, it is possible to calculate how they would have looked like without aliasing.In this master thesis, SENSE has been successfully implemented in PRESTO-CAN. By using normalized convolution in order to refine the sensitivity maps of the receiver coils, images with satisfying quality was able to be reconstructed when reducing the k-space sample rate by a factor of 2, and images of relatively good quality also when the sample rate was reduced by a factor of 4. In this way, this thesis has been able to contribute to the improvement of the temporal resolution of the PRESTO-CAN method. / MRI (Magnetic Resonance Imaging) är en medicinsk avbildningsmetod som använder magnetfält för att framställa bilder av människokroppen. Detta examensarbete kretsar kring en ny inläsningsmetod för 3D-fMRI (functional Magnetic Resonance Imaging) vid namn PRESTO-CAN som använder ett radiellt mönster för att sampla (kx,kz)-planet av k-rummet (frekvensdomänen), och ett kartesiskt samplingsmönster i ky-riktningen. Det radiella samplingsmönstret möjliggör tätare sampling av k-rummets centrala delar, som innehåller den mest grundläggande frekvensinformationen om det inlästa objektets struktur. Detta leder till att en högre temporal upplösning kan uppnås jämfört med andra metoder eftersom det krävs ett mindre antal totala sampel för att få tillräcklig information om hur objektet har ändrats över tid. Eftersom fMRI framförallt används för att övervaka blodflödet i hjärnan innebär ökad temporal upplösning att vi kan följa snabba ändringar i hjärnaktivitet mer effektivt.Den temporala upplösningen kan förbättras ytterligare genom att minska scanningstiden, vilket i sin tur kan uppnås genom att tillämpa parallell avbildning. En metod för parallell avbildning är SENSE (SENSitivity Encoding). Scanningstiden minskas genom att minska samplingstätheten, vilket orsakar vikning i de inlästa bilderna. Vikningen tas bort med SENSE-metoden genom att utnyttja den extra information som tillhandahålls av det faktum att ett flertal olika mottagarspolar med sinsemellan olika känsligheter används vid inläsningen. Genom att mäta upp känsligheterna för de respektive mottagarspolarna och lösa ett ekvationssystem med de vikta bilderna är det möjligt att beräkna hur de skulle ha sett ut utan vikning.I detta examensarbete har SENSE framgångsrikt implementerats i PRESTO-CAN. Genom att använda normaliserad faltning för att förfina mottagarspolarnas känslighetskartor har bilder med tillfredsställande kvalitet varit möjliga att rekonstruera när samplingstätheten av k-rummet minskats med en faktor 2, och bilder med relativt bra kvalitet också när samplingstätheten minskats med en faktor 4. På detta sätt har detta examensarbete kunnat bidra till förbättrandet av PRESTO-CAN-metodens temporala upplösning.