@Article{RI-ASSEMLAL-2011,
author = {Haz-Edine Assemlal and David Tschumperle and Luc Brun and Kaleem Siddiqi},
title = {Recent advances in diffusion MRI modeling: Angular and radial reconstruction},
journal = {Medical image analysis},
year = 2011,
volume = 15,
number = 4,
pages = {369-396},
month = {August},
theme = {misc},
url={pdf:=https://tschumperle.users.greyc.fr/publications/tschumperle_media11.pdf},
abstract="The analysis of the diffusion signal is closely related to
the sampling of the q-space. (a) Full sampling of
the q-space is currently impractical in vivo due to
the significant acquisition time it would imply. (b)
Low angular resolution sampling used in DTI. (c)
High angular resolution sampling (HARDI). (d) Radial
only sampling used in diffusion NMR. (e) Sparse
sampling which combines radial and angular
measurements. auto couleur.bib couleur.bib~ couleur.bib2 fingerprint.bib~ fingerprint.bib.old misc.bib misc.bib~ pattern.bib pattern.bib~ SAVE tmp.tex topologie.bib topologie.bib~ Acquisition time for a diffusion
image at full resolution is approximately 1h. auto couleur.bib couleur.bib~ couleur.bib2 fingerprint.bib~ fingerprint.bib.old misc.bib misc.bib~ pattern.bib pattern.bib~ SAVE tmp.tex topologie.bib topologie.bib~
Direct processing of the data is not reliable due to
the limited number of samples. auto couleur.bib couleur.bib~ couleur.bib2 fingerprint.bib~ fingerprint.bib.old misc.bib misc.bib~ pattern.bib pattern.bib~ SAVE tmp.tex topologie.bib topologie.bib~ Numerous
reconstruction models of the literature are
described in this review. auto couleur.bib couleur.bib~ couleur.bib2 fingerprint.bib~ fingerprint.bib.old misc.bib misc.bib~ pattern.bib pattern.bib~ SAVE tmp.tex topologie.bib topologie.bib~ Three groups of methods
based on the nature of sampling: angular, radial and
combined. Recent advances in diffusion magnetic
resonance image (dMRI) modeling have led to the
development of several state of the art methods for
reconstructing the diffusion signal. These methods
allow for distinct features to be computed, which in
turn reflect properties of fibrous tissue in the
brain and in other organs. A practical consideration
is that to choose among these approaches requires
very specialized knowledge. In order to bridge the
gap between theory and practice in dMRI
reconstruction and analysis we present a detailed
review of the dMRI modeling literature. We place an
emphasis on the mathematical and algorithmic
underpinnings of the subject, categorizing existing
methods according to how they treat the angular and
radial sampling of the diffusion signal. We describe
the features that can be computed with each method
and discuss its advantages and limitations. We also
provide a detailed bibliography to guide the
reader."
}