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• W2098761440 abstract "In diffusion magnetic resonance imaging, images sensitised to water diffusion are acquired by applying magnetic field gradients in different directions. In order to reduce the scanning time so that the procedure is clinically plausible, it is necessary to limit the number of directions, and thus the spatial and angular resolution of the image. Missing data is then reconstructed in the post-processing step. However, the measurement noise can be significant and affect adversely the reconstructed signal. An elegant way of dealing with this problem is to use regularisation during reconstruction. Depending on the strength of regularisation applied, it may lead to an under- or over-regularised solution. Previous works have established the L-curve analysis as a procedure for automatic selection of regularisation strength in diffusion signal reconstruction. In this paper the L-curve-based approach is compared with a recently proposed method based on ground truth validation." @default.
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• W2098761440 date "2013-01-01" @default.
• W2098761440 modified "2023-10-17" @default.
• W2098761440 title "Tikhonov regularisation in diffusion signal estimation" @default.
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• W2098761440 hasPublicationYear "2013" @default.
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