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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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