Search Results - Technical Notes—Computer Processing and Modeling*

Myelin water fraction mapping from multiple echo spin echoes and an independent B1+ map by Mehdizadeh, Nima, Wilman, Alan H.

“…Purpose Myelin water fraction (MWF) is often obtained from a multiple echo spin echo (MESE) sequence using multi‐component T2 fitting with non‐negative least…”
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Learning a preconditioner to accelerate compressed sensing reconstructions in MRI by Koolstra, Kirsten, Remis, Rob

“…Purpose To learn a preconditioner that accelerates parallel imaging (PI) and compressed sensing (CS) reconstructions. Methods A convolutional neural network…”
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Personalized synthetic MR imaging with deep learning enhancements by Pal, Subrata, Dutta, Somak, Maitra, Ranjan

“…Purpose Personalized synthetic MRI (syn‐MRI) uses MR images of an individual subject acquired at a few design parameters (echo time, repetition time, flip…”
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Hybrid data fidelity term approach for quantitative susceptibility mapping by Lambert, Mathias, Tejos, Cristian, Langkammer, Christian, Milovic, Carlos

“…Purpose Susceptibility maps are usually derived from local magnetic field estimations by minimizing a functional composed of a data consistency term and a…”
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Agent-based modeling : the Santa Fe Institute Artificial Stock Market model revisited by Ehrentreich, Norman

“…This book reconciles the existence of technical trading with the Efficient Market Hypothesis…”
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Processing computer tomography bone data for prosthetic finite element modeling: a technical note by Saxena, Rakesh, Zachariah, Santosh G, Sanders, Joan E

“…) data for use in prosthetic finite element modeling. A snake algorithm is implemented to overcome challenges of bone-soft tissue edge detection common in this application…”
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