Evaluation of q-space sampling strategies for the diffusion magnetic resonance imaging

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Abstract

We address the problem of efficient sampling of the diffusion space for the Diffusion Magnetic Resonance Imaging (dMRI) modality. While recent scanner improvements enable the acquisition of more and more detailed images, it is still unclear which q-space sampling strategy gives the best performance. We evaluate several q-space sampling distributions by an approach based on the approximation of the MR signal by a series expansion of Spherical Harmonics and Laguerre-Gaussian functions. With the help of synthetic experiments, we identify a subset of sampling distributions which leads to the best reconstructed data. © 2009 Springer-Verlag.

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APA

Assemlal, H. E., Tschumperlé, D., & Brun, L. (2009). Evaluation of q-space sampling strategies for the diffusion magnetic resonance imaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5762 LNCS, pp. 406–414). https://doi.org/10.1007/978-3-642-04271-3_50

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