TY - GEN
T1 - Non-rigid groupwise image registration for motion compensation in quantitative MRI
AU - Huizinga, Wyke
AU - Poot, Dirk H.J.
AU - Guyader, Jean Marie
AU - Smit, Henk
AU - Van Kranenburg, Matthijs
AU - Van Geuns, Robert Jan M.
AU - Uitterdijk, André
AU - Van Beusekom, Heleen M.M.
AU - Coolen, Bram F.
AU - Leemans, Alexander
AU - Niessen, Wiro J.
AU - Klein, Stefan
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Quantitative magnetic resonance imaging (qMRI) aims to extract quantitative parameters representing tissue properties from a series of images by modeling the image acquisition process. This requires the images to be spatially aligned but, due to patient motion, anatomical structures in the consecutive images may be misaligned. In this work, we propose a groupwise non-rigid image registration method for motion compensation in qMRI. The method minimizes a dissimilarity measure based on principal component analysis (PCA), exploiting the fact that intensity changes can be described by a low-dimensional acquisition model. Using an unbiased groupwise formulation of the registration problem, there is no need to choose a reference image as in conventional pairwise approaches. The method was evaluated on three applications: modified Look-Locker inversion recovery T1 mapping in a porcine myocardium, black-blood variable flip-angle T1 mapping in the carotid artery region, and apparent diffusion coefficient (ADC) mapping in the abdomen. The method was compared to a conventional pairwise alignment that uses a mutual information similarity measure. Registration accuracy was evaluated by computing precision of the estimated parameters of the qMRI model. The results show that the proposed method performs equally well or better than an optimized pairwise approach and is therefore a suitable motion compensation method for a wide variety of qMRI applications.
AB - Quantitative magnetic resonance imaging (qMRI) aims to extract quantitative parameters representing tissue properties from a series of images by modeling the image acquisition process. This requires the images to be spatially aligned but, due to patient motion, anatomical structures in the consecutive images may be misaligned. In this work, we propose a groupwise non-rigid image registration method for motion compensation in qMRI. The method minimizes a dissimilarity measure based on principal component analysis (PCA), exploiting the fact that intensity changes can be described by a low-dimensional acquisition model. Using an unbiased groupwise formulation of the registration problem, there is no need to choose a reference image as in conventional pairwise approaches. The method was evaluated on three applications: modified Look-Locker inversion recovery T1 mapping in a porcine myocardium, black-blood variable flip-angle T1 mapping in the carotid artery region, and apparent diffusion coefficient (ADC) mapping in the abdomen. The method was compared to a conventional pairwise alignment that uses a mutual information similarity measure. Registration accuracy was evaluated by computing precision of the estimated parameters of the qMRI model. The results show that the proposed method performs equally well or better than an optimized pairwise approach and is therefore a suitable motion compensation method for a wide variety of qMRI applications.
KW - ADC mapping
KW - groupwise image registration
KW - motion compensation
KW - principal component analysis
KW - quantitative MRI
UR - http://www.scopus.com/inward/record.url?scp=84903734521&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-08554-8_19
DO - 10.1007/978-3-319-08554-8_19
M3 - Conference contribution
AN - SCOPUS:84903734521
SN - 9783319085531
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 184
EP - 193
BT - Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings
PB - Springer-Verlag
T2 - 6th International Workshop on Biomedical Image Registration, WBIR 2014
Y2 - 7 July 2014 through 8 July 2014
ER -