Improved Shinnar-Le Roux algorithm

Selective excitation pulses are widely used in magnetic resonance imaging in order to excite predetermined slices of the body under examination. Such pulses are optimally designed by means of the Shinnar-Le Roux algorithm. In this paper, we show that under minimal assumptions, the complexity and computing cost of the original Shinnar-Le Roux algorithm can be drastically reduced. We further propose an improved version of the algorithm, involving only real quantities, which is both easier to implement and faster to execute, so it is suitable for implementation at the hardware level, in the context of a real-time fully digital magnetic resonance transceiver.     

A rotational approach to localized SPAMM 1-1 tagging

Magnetic resonance tagging usually relies on controlling the phase dispersion of the transverse magnetization component. Phase dispersion is, however, affected by the inherent phase of selective excitation pulses, thus limiting their combination with tagging sequences to the application of refocusable pulses, as in the localized spatial modulation of magnetization (L-SPAMM) technique. In this study, we examine the effect of selective excitation pulses on a L-SPAMM 1-1 sequence, showing that in the case of two identical pulses the phase component is canceled out, and thus preemphasis and refocus gradients are not needed, allowing us to take advantage of a constant gradient throughout the tagging sequence, and also that one might choose nonrefocusable maximum and minimum phase pulses.     

A parallel multi-configuration self-consistent field algorithm

A scalable multi-configuration self-consistent field (MCSCF) algorithm is described. The method for optimizing the orbital and configurational parameters is based upon the two-step Newton–Raphson approach with an augmented orbital Hessian matrix. A single copy of the two-electron integrals in the molecular orbital basis is distributed over the memory of all processors. Storage of the augmented Hessian is avoided by re-computing its elements as needed. A replicated data approach is used to parallelize the configuration interaction step. Scalability to 1024 processors is demonstrated.