TY - GEN
T1 - Multiple Q-shell ODF reconstruction in Q-ball imaging
AU - Aganj, Iman
AU - Lenglet, Christophe
AU - Sapiro, Guillermo
AU - Yacoub, Essa
AU - Ugurbil, Kamil
AU - Harel, Noam
PY - 2009
Y1 - 2009
N2 - Q-ball imaging (QBI) is a high angular resolution diffusion imaging (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (ODF, the probability of diffusion in a given direction) from q-ball uses linear radial projection, neglecting the change in the volume element along the ray, thereby resulting in distributions different from the true ODFs. A new technique has been recently proposed that, by considering the solid angle factor, uses the mathematically correct definition of the ODF and results in a dimensionless and normalized ODF expression from a single q-shell. In this paper, we extend this technique in order to exploit HARDI data from multiple q-shells. We consider the more flexible multi-exponential model for the diffusion signal, and show how to efficiently compute the ODFs in constant solid angle. We describe our method and demonstrate its improved performance on both artificial and real HARDI data.
AB - Q-ball imaging (QBI) is a high angular resolution diffusion imaging (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (ODF, the probability of diffusion in a given direction) from q-ball uses linear radial projection, neglecting the change in the volume element along the ray, thereby resulting in distributions different from the true ODFs. A new technique has been recently proposed that, by considering the solid angle factor, uses the mathematically correct definition of the ODF and results in a dimensionless and normalized ODF expression from a single q-shell. In this paper, we extend this technique in order to exploit HARDI data from multiple q-shells. We consider the more flexible multi-exponential model for the diffusion signal, and show how to efficiently compute the ODFs in constant solid angle. We describe our method and demonstrate its improved performance on both artificial and real HARDI data.
UR - http://www.scopus.com/inward/record.url?scp=70749153357&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70749153357&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04271-3_52
DO - 10.1007/978-3-642-04271-3_52
M3 - Conference contribution
C2 - 20426140
AN - SCOPUS:84880326196
SN - 3642042708
SN - 9783642042706
VL - 5762 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 423
EP - 431
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Y2 - 20 September 2009 through 24 September 2009
ER -