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Improved tractography using asymmetric fibre orientation distributions

Bastiani, Matteo; Cottaar, Michiel; Dikranian, Krikor; Ghosh, Aurobrata; Zhang, Hui; Alexander, Daniel C.; Behrens, Timothy E.; Jbabdi, Saad; Sotiropoulos, Stamatios N.


Matteo Bastiani

Michiel Cottaar

Krikor Dikranian

Aurobrata Ghosh

Hui Zhang

Daniel C. Alexander

Timothy E. Behrens

Saad Jbabdi


Diffusion MRI allows us to make inferences on the structural organisation of the brain by mapping water diffusion to white matter microstructure. However, such a mapping is generally ill-defined; for instance, diffusion measurements are antipodally symmetric (diffusion along x and –x are equal), whereas the distribution of fibre orientations within a voxel is generally not symmetric. Therefore, different sub-voxel patterns such as crossing, fanning, or sharp bending, cannot be distinguished by fitting a voxel-wise model to the signal. However, asymmetric fibre patterns can potentially be distinguished once spatial information from neighbouring voxels is taken into account. We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods). Importantly, we further design and implement a tractography algorithm that utilises the estimated A-fods, since the commonly used streamline tractography paradigm cannot directly take advantage of the new information. We assess performance using ultra-high resolution histology data where we can compare true orientation distributions against sub-voxel fibre patterns estimated from down-sampled data. Finally, we explore the benefits of A-fods-based tractography using in vivo data by evaluating agreement of tractography predictions with connectivity estimates made using different in-vivo modalities. The proposed approach can reliably estimate complex fibre patterns such as sharp bending and fanning, which voxel-wise approaches cannot estimate. Moreover, histology-based and in-vivo results show that the new framework allows more accurate tractography and reconstruction of maps quantifying (symmetric and asymmetric) fibre complexity.


Bastiani, M., Cottaar, M., Dikranian, K., Ghosh, A., Zhang, H., Alexander, D. C., …Sotiropoulos, S. N. (2017). Improved tractography using asymmetric fibre orientation distributions. NeuroImage, 158,

Journal Article Type Article
Acceptance Date Jun 21, 2017
Online Publication Date Jun 29, 2017
Publication Date Sep 30, 2017
Deposit Date Jul 6, 2017
Publicly Available Date Jul 6, 2017
Journal NeuroImage
Print ISSN 1053-8119
Electronic ISSN 1095-9572
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 158
Keywords Diffusion MRI, Tractography, Structural connectivity, Asymmetry, Connectome
Public URL
Publisher URL
Copyright Statement Copyright information regarding this work can be found at the following address:


Sotiropoulos Improved.pdf (5.3 Mb)

Copyright Statement
Copyright information regarding this work can be found at the following address:

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