Purpose: Joint design of minimum duration RF pulses and slice-selective gradient shapes for MRI via time optimal control with strict physical constraints, and its application to simultaneous multislice imaging.
Theory And Methods: The minimization of the pulse duration is cast as a time optimal control problem with inequality constraints describing the refocusing quality and physical constraints. It is solved with a bilevel method, where the pulse length is minimized in the upper level, and the constraints are satisfied in the lower level. To address the inherent nonconvexity of the optimization problem, the upper level is enhanced with new heuristics for finding a near global optimizer based on a second optimization problem.
Results: A large set of optimized examples shows an average temporal reduction of 87.1% for double diffusion and 74% for turbo spin echo pulses compared to power independent number of slices pulses. The optimized results are validated on a 3T scanner with phantom measurements.
Conclusion: The presented design method computes minimum duration RF pulse and slice-selective gradient shapes subject to physical constraints. The shorter pulse duration can be used to decrease the effective echo time in existing echo-planar imaging or echo spacing in turbo spin echo sequences.
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http://dx.doi.org/10.1002/mrm.27124 | DOI Listing |
Best Pract Res Clin Anaesthesiol
September 2024
Department of Anesthesiology, University Hospital Basel, Basel, Switzerland.
The issue of obesity continues to reach new levels globally, affecting individuals across the age continuum. Obesity in pregnancy is associated with myriad comorbidities which may negatively impact the fetus, particularly dysfunctional labor and failure to progress ending in unplanned cesarean delivery. Neuraxial anesthesia represents the gold standard for cesarean delivery anesthesia and is increasingly beneficial for obese patients due to the risk of difficult airway.
View Article and Find Full Text PDFBest Pract Res Clin Anaesthesiol
September 2024
K. Bicetre School of Medicine, Paris-Saclay University, Département d'Anesthésie, Hôpital Antoine Béclère - APHP.Université Paris-Saclay, 157 rue de la porte de Trivaux, 92140, CLAMART, France. Electronic address:
This article offers a comprehensive clinical update on best practices for neuraxial and general anesthesia in cesarean delivery, the most frequently performed major surgical procedure globally. Current evidence-based strategies to address common anesthetic challenges, such as maternal hypotension and intraoperative breakthrough pain, are discussed in detail. Practical approaches for optimizing maternal hemodynamic stability, including the use of vasopressors, fluid management and maternal positioning, are reviewed.
View Article and Find Full Text PDFFront Genet
December 2024
School of information engineering, Jingdezhen Ceramic University, Jingdezhen, China.
The early symptoms of hepatocellular carcinoma patients are often subtle and easily overlooked. By the time patients exhibit noticeable symptoms, the disease has typically progressed to middle or late stages, missing optimal treatment opportunities. Therefore, discovering biomarkers is essential for elucidating their functions for the early diagnosis and prevention.
View Article and Find Full Text PDFFront Health Serv
December 2024
Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Introduction: Clinicians are the conduits of high-quality care delivery. Clinicians have driven advancements in pharmacotherapeutics, devices, and related interventions and improved morbidity and mortality in patients with congestive heart failure over the past decade. Yet, the management of congestive heart failure has become extraordinarily complex and has fueled recommendations from the American Heart Association and the American College of Cardiology to optimize the composition of the care team to reduce the health, economic, and the health system burden of high lengths of stay and hospital charges.
View Article and Find Full Text PDFCurrent neural network models of primate vision focus on replicating overall levels of behavioral accuracy, often neglecting perceptual decisions' rich, dynamic nature. Here, we introduce a novel computational framework to model the dynamics of human behavioral choices by learning to align the temporal dynamics of a recurrent neural network (RNN) to human reaction times (RTs). We describe an approximation that allows us to constrain the number of time steps an RNN takes to solve a task with human RTs.
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