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Abstract #3885

Bayesian Experimental Design for Multi-Parametric T1/T2 Relaxometry and Diffusion

David Owen1, Andrew Melbourne2, Magdalena Sokolska3, David L Thomas2,4, Jonathan Rohrer4, and Sebastien Ourselin2

1Translational Imaging Group, University College London, London, United Kingdom, 2Translational Imaging Group, University College London, 3Department of Medical Physics, University College London Hospitals, 4Dementia Research Centre, University College London

Multi-parametric imaging, such as joint relaxometry and diffusion, can allow for a time-efficient measurement of several parameters of interest. However, it is unclear how best to make use of valuable scanner time when using such novel imaging techniques. In this work, we explore how Bayesian experimental design can be used to derive a maximally time-efficient joint imaging experiment.

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