Browsing by Author "Mir, R"

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    Fast three-dimensional k-space trajectory design using missile guidance ideas
    (WILEY, 2004) Mir, R; Guesalaga, A; Spiniak, J; Guarini, M; Irarrazaval, P
    Three-dimensional (3D) k-space trajectories are needed to acquire volumetric images in MRI. While scan time is determined by the trajectory efficiency, image quality and distortions depend on the shape of the trajectories. There are several 3D trajectory strategies for sampling the k-space using rectilinear or curve schemes. Since there is no evidence about their optimality in terms of image quality and acquisition time, a new design method based on missile guidance ideas is explored. Since air-to-air missile guidance shares similar goals and constraints with the problem of k-space trajectory design, a control approach for missiles is used to design a 3D trajectory. The k-space is divided into small cubes, and each one is treated as a target to be sampled. The main goal is to cover the entire space as quickly and efficiently as possible, with good performance under different conditions. This novel design method is compared to other trajectories using simulated and real data. As an example, a trajectory that requires 0.11 times the number of shots needed by the cylindrical 3DFT acquisition was designed. This trajectory requires more shots (1.66 times) than the stack of spirals, but behaves better under nonideal conditions, such as off-resonance and motion. (C) 2004 Wiley-Liss, Inc.
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    Three dimensional k-space trajectory design using genetic algorithms
    (ELSEVIER SCIENCE INC, 2003) Sabat, S; Mir, R; Guarini, M; Guesalaga, A; Irarrazaval, P
    Image quality and total scan time in MRI are determined in large part by the trajectory employed to sample the Fourier space. Each trajectory has different properties like coverage of k-space, scan time, sensitivity to off-resonance conditions, etc. These properties are often contradictory, therefore a universal optimal trajectory does not exist and ultimately, it will depend on the image characteristics sought. Most trajectories used today are designed based on intuition and k-space analysis more than with optimization methods. This work presents a 3D k-space trajectory design method based on Genetic Algorithm optimization. Genetic Algorithms have been chosen because they are particularly good for searching large solution spaces. They emulate the natural evolutionary process allowing better offsprings to survive. The objective function searches the maximum of the trajectory's k-space coverage subject to hardware constraints for a fixed scanning time using the trajectory's torsion as its optimization variable.
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    Undersampling k-space using fast progressive 3D trajectories
    (WILEY, 2005) Spiniak, J; Guesalaga, A; Mir, R; Guarini, M; Irarrazaval, P
    In 3D MRI, sampling k-space with traditional trajectories can be excessively time-consuming. Fast imaging trajectories are used in an attempt to efficiently cover the k-space and reduce the scan time without significantly affecting the image quality. In many applications, further reductions in scan time can be achieved via undersampling of the k-space; however, no clearly optimal method exists. In most 3D trajectories the k-space is divided into regions that are sampled with shots that share a common geometry (e.g., spirals). A different approach is to design trajectories that gradually but uniformly cover the k-space. In the current work, successive shots progressively add sampled regions to the 3D frequency space. By cutting the sequence short, a natural undersampled method is obtained. This can be particularly efficient because in these types of trajectories the contribution of new information by later shots is less significant. In this work the performance of progressive trajectories for different degrees of undersampling is assessed with trajectories based on missile guidance (MG) ideas. The results show that the approach can be efficient in terms of reducing the scan time, and performs better than the stack of spirals (SOS) technique, particularly under nonideal conditions.