Robust myelin water imaging from multi-echo T2 data using second-order Tikhonov regularization with control points

Myelin water imaging is an MRI technique used to quantify myelination in the brain. The state-of-the-art reconstruction method is based on non-negative least squares optimization with zero-order Tikhonov regularization. In this study, a second-order Tikhonov regularization approach with control points was examined. This penalty term is more efficient for promoting smooth solutions while minimizing the contamination between myelin and non-myelin components. The performance of the proposed algorithm was investigated on in-vivo and ex-vivo multi-echo T2 data. It exhibited a higher correlation with histology than the state-of-the-art method. Its stability was studied using scan-rescan data.


Presented at:
27th ISMRM Annual Meeting, Montréal, Canada, Mai 11-16, 2019
Year:
May 11 2019
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 Record created 2020-01-02, last modified 2020-04-20

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