Multicomponent T2 estimation with stimulated echo correction
This tool is designed to assist users in the estimation of multiple relaxation components from MRI T2 weighted spin-echo data such as that produced by a Carr-Purcell-Meiboom-Gill (CPMG) sequence. This problem is important to study myelin content in white matter diseases such as multiple sclerosis.
Stimulated echoes arising from non-ideal flip angles are accounted for using the Extended Phase Graph (EPG) algorithm. The distribution is modelled as a small number of discrete components and a Bayesian estimation algorithm is provided to determine the weights and locations of the components as well as the actual flip angle. This algorithm outperforms iterative gradient descent based approaches.
The details of the algorithm are given the following paper:
Layton, K. J. et al. (2013) Modelling and Estimation of Multicomponent T2 Distributions, IEEE Transactions on Medical Imaging 32:1423-1434
Stimulated echoes arising from non-ideal flip angles are accounted for using the Extended Phase Graph (EPG) algorithm. The distribution is modelled as a small number of discrete components and a Bayesian estimation algorithm is provided to determine the weights and locations of the components as well as the actual flip angle. This algorithm outperforms iterative gradient descent based approaches.
The details of the algorithm are given the following paper:
Layton, K. J. et al. (2013) Modelling and Estimation of Multicomponent T2 Distributions, IEEE Transactions on Medical Imaging 32:1423-1434
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multi_t2: Initial source code release release
MulticomponentT2Bayesian.zip posted by Kelvin Layton on Jul 29, 2013