Abstract #3885

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

David Owen¹, Andrew Melbourne², Magdalena Sokolska³, David L Thomas^2,4, 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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