@article{QIMS38368,
author = {Maximilian N. Diefenbach and Chunlei Liu and Dimitrios C. Karampinos},
title = {Generalized parameter estimation in multi-echo gradient-echo-based chemical species separation},
journal = {Quantitative Imaging in Medicine and Surgery},
volume = {10},
number = {3},
year = {2020},
keywords = {},
abstract = {To develop a generalized formulation for multi-echo gradient-echo-based chemical species separation for all MR signal models described by a weighted sum of complex exponentials with phases linear in the echo time. Constraints between estimation parameters in the signal model were abstracted into a matrix formulation of a generic parameter gradient. The signal model gradient was used in a parameter estimation algorithm and the Fisher information matrix. The general formulation was tested in numerical simulations and against literature and in vivo results. The proposed gradient-based parameter estimation and experimental design framework is universally applicable over the whole class of signal models using the matrix abstraction of the signal model-specific parameter constraints as input. Several previous results in magnetic-field mapping and water-fat imaging with different models could successfully be replicated with the same framework and only different input matrices. A framework for generalized parameter estimation in multi-echo gradient-echo MR signal models of multiple chemical species was developed and validated and its software version is freely available online.},
issn = {2223-4306}, url = {https://qims.amegroups.org/article/view/38368}
}