ABSTRACT
A method - PA-keyhole - for 2D/3D dynamic magnetic resonance imaging with radial scanning is proposed. PA-keyhole exploits the inherent strong oversampling in the center of k-space, which contains crucial temporal information regarding contrast evolution. The method is based on: (1). a rearrangement of the temporal order of 2D/3D isotropic distributions of trajectories during the scan into subdistributions according to the desired time resolution, (2). a new post-acquisition keyhole approach based on the replacement of the central disk/sphere in k-space using data solely from a subdistribution, and (3). reconstruction of 2D/3D dynamic (time-resolved) images using 2D/3D-gridding with Pipe's approach to the sampling density compensation and 2D/3D-IFFT. The scan time is not increased with respect to a conventional 2D/3D radial scan of the same spatial resolution; in addition, one benefits from the dynamic information. The abilities of PA-keyhole and the sliding window techniques to restore simulated dynamic contrast changes are compared. Results are shown both for 2D and 3D dynamic imaging using experimental data. An application to in-vivo ventilation of rat lungs using hyperpolarized helium is demonstrated.
Subject(s)
Algorithms , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging, Cine/methods , Signal Processing, Computer-Assisted , Animals , Brain/anatomy & histology , Lung/anatomy & histology , Lung/physiology , Magnetic Resonance Imaging, Cine/instrumentation , Male , Phantoms, Imaging , Pulmonary Ventilation/physiology , Quality Control , Rats , Rats, Sprague-DawleyABSTRACT
We have worked on multi-dimensional magnetic resonance imaging (MRI) data acquisition and related image reconstruction methods that aim at reducing the MRI scan time. To achieve this scan-time reduction we have combined the approach of 'increasing the speed' of k-space acquisition with that of 'deliberately omitting' acquisition of k-space trajectories (sparse sampling). Today we have a whole range of (sparse) sampling distributions and related reconstruction methods. In the context of a European Union Training and Mobility of Researchers project we have decided to integrate all methods into one coordinating software system. This system meets the requirements that it is highly structured in an object-oriented manner using the Unified Modeling Language and the Java programming environment, that it uses the client-server approach, that it allows multi-client communication sessions with facilities for sharing data and that it is a true distributed computing system with guaranteed reliability using core activities of the Java Jini package.
