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  Optimal DSI reconstruction parameter recommendations: Better ODFs and better connectivity

Paquette, M., Gilbert, G., & Descoteaux, M. (2016). Optimal DSI reconstruction parameter recommendations: Better ODFs and better connectivity. NeuroImage, 142, 1-13. doi:10.1016/j.neuroimage.2016.07.048.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-B8C8-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-B8C9-8
Genre: Journal Article

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 Creators:
Paquette, Michael1, Author              
Gilbert, Guillaume1, Author
Descoteaux, Maxime1, Author
Affiliations:
1External Organizations, ou_persistent22              

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Free keywords: Diffusion MRI; Diffusion spectrum imaging; Orientation distribution function; Tractography; Tractometer; Connectivity
 Abstract: Diffusion Spectrum Imaging (DSI) has been used for tractography in several publicly available software and a number of recent high impact publications. However, there are several important theoretical, numerical and practical considerations that are often ignored. We revisit the theoretical and state-of-the-art processing steps necessary to go from the DSI signal to the diffusion orientation distribution function (dODF) used by tractography. We show that the parameters in the reconstruction have huge impact on the reconstruction quality and that, while there is no consensus about what they should be, the parameters we most often see in the literature are not optimal. We provide applicable recommendations that improve the accuracy of extracted local orientations and improve accuracy of global connectivity as measured by the Tractometer, a tractography online evaluation system. These recommendations come for “free” as they are applicable to all existing DSI data and do not require a significant increase in computation time. Hence, this paper highlights the do's and dont's of DSI reconstruction.

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Language(s): eng - English
 Dates: 2014-10-012016-07-242016-07-302016-11-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 142 Sequence Number: - Start / End Page: 1 - 13 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166