Abstract #0447
Simultaneous group-wise rigid registration and Maximum Likelihood T 1 estimation for T 1 mapping
Gabriel Ramos-Llordn 1 , Arnold J. den Dekker 1,2 , Gwendolyn Van Steenkiste 1 , Johan Van Audekerke 3 , Marleen Verhoye 3 , and Jan Sijbers 1
1
iMinds-Vision Lab, University of Antwerp,
Antwerp, Belgium,
2
Delft
Center for Systems and Control, Delft University of
Technology, Delft, Netherlands,
3
Bio-Imaging
Lab, University of Antwerp, Antwerp, Belgium
In T
1
mapping,
to prevent motion artifacts, alignment of the acquired T
1
weighted
images is required. Commonly, image registration is
accomplished prior to T
1
map
estimation. However, this two-step approach introduces
bias in the T
1
estimation
due to inaccurate motion estimation and image
interpolation. We propose a simultaneous group-wise
rigid registration and T
1
estimation
method using a Maximum Likelihood (ML) approach for
brain T
1
mapping,
thereby constructing a unified framework and
circumventing the problems of the conventional two-step
approach. Results with synthetic and real data
demonstrate that the proposed method outperforms the
conventional two-step approach.
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