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Diffusion orientation transform revisited

Authors :
Erick J. Canales-Rodríguez
Lester Melie-Garcia
Chun-Hung Yeh
Kuan Hung Cho
Ching Po Lin
Yasser Iturria-Medina
Source :
NeuroImage. 49:1326-1339
Publication Year :
2010
Publisher :
Elsevier BV, 2010.

Abstract

Diffusion orientation transform (DOT) is a powerful imaging technique that allows the reconstruction of the microgeometry of fibrous tissues based on diffusion MRI data. The three main error sources involving this methodology are the finite sampling of the q-space, the practical truncation of the series of spherical harmonics and the use of a mono-exponential model for the attenuation of the measured signal. In this work, a detailed mathematical description that provides an extension to the DOT methodology is presented. In particular, the limitations implied by the use of measurements with a finite support in q-space are investigated and clarified as well as the impact of the harmonic series truncation. Near- and far-field analytical patterns for the diffusion propagator are examined. The near-field pattern makes available the direct computation of the probability of return to the origin. The far-field pattern allows probing the limitations of the mono-exponential model, which suggests the existence of a limit of validity for DOT. In the regimen from moderate to large displacement lengths the isosurfaces of the diffusion propagator reveal aberrations in form of artifactual peaks. Finally, the major contribution of this work is the derivation of analytical equations that facilitate the accurate reconstruction of some orientational distribution functions (ODFs) and skewness ODFs that are relatively immune to these artifacts. The new formalism was tested using synthetic and real data from a phantom of intersecting capillaries. The results support the hypothesis that the revisited DOT methodology could enhance the estimation of the microgeometry of fiber tissues.

Details

ISSN :
10538119
Volume :
49
Database :
OpenAIRE
Journal :
NeuroImage
Accession number :
edsair.doi.dedup.....9db9cc2bcffeb8b778358789e9d46abe
Full Text :
https://doi.org/10.1016/j.neuroimage.2009.09.067