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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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LARO: Learned acquisition and reconstruction optimization to accelerate quantitative susceptibility mapping.

Jinwei Zhang1, Pascal Spincemaille2, Hang Zhang3

  • 1Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.

Neuroimage
|January 20, 2023
PubMed
Summary

Learned Acquisition and Reconstruction Optimization (LARO) accelerates quantitative susceptibility mapping (QSM) by optimizing k-space sampling and using a deep learning reconstruction. This novel framework enhances multi-echo gradient echo imaging efficiency and image quality.

Failed At:

2026-06-19T13:49:00.867799+00:00

Keywords:
Multi-echo gradient echoQuantitative susceptibility mappingSampling pattern optimizationUnrolled reconstruction

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