TY - GEN
T1 - Motion correction and parameter estimation in dceMRI sequences
T2 - 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
AU - Bhushan, Manav
AU - Schnabel, Julia A.
AU - Risser, Laurent
AU - Heinrich, Mattias P.
AU - Brady, J. Michael
AU - Jenkinson, Mark
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - We present a novel Bayesian framework for non-rigid motion correction and pharmacokinetic parameter estimation in dceMRI sequences which incorporates a physiological image formation model into the similarity measure used for motion correction. The similarity measure is based on the maximization of the joint posterior probability of the transformations which need to be applied to each image in the dataset to bring all images into alignment, and the physiological parameters which best explain the data. The deformation framework used to deform each image is based on the diffeomorphic logDemons algorithm. We then use this method to co-register images from simulated and real dceMRI data-sets and show that the method leads to an improvement in the estimation of physiological parameters as well as improved alignment of the images.
AB - We present a novel Bayesian framework for non-rigid motion correction and pharmacokinetic parameter estimation in dceMRI sequences which incorporates a physiological image formation model into the similarity measure used for motion correction. The similarity measure is based on the maximization of the joint posterior probability of the transformations which need to be applied to each image in the dataset to bring all images into alignment, and the physiological parameters which best explain the data. The deformation framework used to deform each image is based on the diffeomorphic logDemons algorithm. We then use this method to co-register images from simulated and real dceMRI data-sets and show that the method leads to an improvement in the estimation of physiological parameters as well as improved alignment of the images.
UR - http://www.scopus.com/inward/record.url?scp=82255185831&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23623-5_60
DO - 10.1007/978-3-642-23623-5_60
M3 - Conference contribution
C2 - 22003652
AN - SCOPUS:82255185831
SN - 9783642236228
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 476
EP - 483
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
Y2 - 18 September 2011 through 22 September 2011
ER -