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arxiv: 2009.07376 · v1 · pith:YI4ROSORnew · submitted 2020-09-15 · 📡 eess.SP

Q-space quantitative diffusion MRI measures using a stretched-exponential representation

classification 📡 eess.SP
keywords diffusionq-spacerepresentationstretched-exponentialdisplacementmeanmeasuresnon-gaussian
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Diffusion magnetic resonance imaging (dMRI) is a relatively modern technique used to study tissue microstructure in a non-invasive way. Non-Gaussian diffusion representation is related to the restricted diffusion and can provide information about the underlying tissue properties. In this paper, we analytically derive $n$-th order statistics of the signal considering a stretched-exponential representation of the diffusion. Then, we retrieve the Q-space quantitative measures such as the Return-To-the-Origin Probability (RTOP), Q-space mean square displacement (QMSD), Q-space mean fourth-order displacement (QMFD). The stretched-exponential representation enables the handling of the diffusion contributions from a higher $b$-value regime under a non-Gaussian assumption, which can be useful in diagnosing or prognosis of neurodegenerative diseases in the early stages. Numerical implementation of the method is freely available at https://github.com/TPieciak/Stretched.

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