TY - JOUR
T1 - Co-registration of white matter tractographies by adaptive-mean-shift and gaussian mixture modeling
AU - Zvitia, Orly
AU - Mayer, Arnaldo
AU - Shadmi, Ran
AU - Miron, Shmuel
AU - Greenspan, Hayit K.
N1 - Funding Information:
Manuscript received May 15, 2009; revised May 15, 2009; accepted July 14, 2009. First published August 25, 2009; current version published January 04, 2010. This work was supported in part by a Strategic Research Directions Grant from the Israeli Ministry of Sciences. Asterisk indicates corresponding author. O. Zvitia, R. Shadmi, and H. K. Greenspan are with the Department of Biomedical Engineering, Tel-Aviv University, Ramat-Aviv 69978, Israel (e-mail: [email protected]; [email protected]; [email protected]). *A. Mayer is with the Department of Biomedical Engineering, Tel-Aviv University, Ramat-Aviv 69978, Israel (e-mail: [email protected]). S. Miron is with the Multiple Sclerosis Center, Sheba Hospital, Tel-Hashomer 52621, Israel (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TMI.2009.2029097
PY - 2010/1
Y1 - 2010/1
N2 - In this paper, we present a robust approach to the registration of white matter tractographies extracted from diffusion tensor-magnetic resonance imaging scans. The fibers are projected into a high dimensional feature space based on the sequence of their 3-D coordinates. Adaptive mean-shift clustering is applied to extract a compact set of representative fiber-modes (FM). Each FM is assigned to a multivariate Gaussian distribution according to its population thereby leading to a Gaussian mixture model (GMM) representation for the entire set of fibers. The registration between two fiber sets is treated as the alignment of two GMMs and is performed by maximizing their correlation ratio. A nine-parameters affine transform is recovered and eventually refined to a twelve-parameters affine transform using an innovative mean-shift based registration refinement scheme presented in this paper. The validation of the algorithm on synthetic intrasubject data demonstrates its robustness to interrupted and deviating fiber artifacts as well as outliers. Using real intrasubject data, a comparison is conducted to other intensity based and fiber-based registration algorithms, demonstrating competitive results. An option for tracking-in-time, on specific white matter fiber tracts, is also demonstrated on the real data.
AB - In this paper, we present a robust approach to the registration of white matter tractographies extracted from diffusion tensor-magnetic resonance imaging scans. The fibers are projected into a high dimensional feature space based on the sequence of their 3-D coordinates. Adaptive mean-shift clustering is applied to extract a compact set of representative fiber-modes (FM). Each FM is assigned to a multivariate Gaussian distribution according to its population thereby leading to a Gaussian mixture model (GMM) representation for the entire set of fibers. The registration between two fiber sets is treated as the alignment of two GMMs and is performed by maximizing their correlation ratio. A nine-parameters affine transform is recovered and eventually refined to a twelve-parameters affine transform using an innovative mean-shift based registration refinement scheme presented in this paper. The validation of the algorithm on synthetic intrasubject data demonstrates its robustness to interrupted and deviating fiber artifacts as well as outliers. Using real intrasubject data, a comparison is conducted to other intensity based and fiber-based registration algorithms, demonstrating competitive results. An option for tracking-in-time, on specific white matter fiber tracts, is also demonstrated on the real data.
KW - Brain
KW - Diffusion tensor imaging (DTI)
KW - Registration
KW - Tractography
UR - http://www.scopus.com/inward/record.url?scp=73849119648&partnerID=8YFLogxK
U2 - 10.1109/TMI.2009.2029097
DO - 10.1109/TMI.2009.2029097
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AN - SCOPUS:73849119648
SN - 0278-0062
VL - 29
SP - 132
EP - 145
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 1
M1 - 5223611
ER -