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Abstract #1594

A novel method for the detection of the number of compartments in diffusion MRI data

Emma Metcalfe-Smith1,2,3, Niloufar Zarinabad2,3, Jan Novak2,3, Hamid Dehghani1,4, and Andrew Peet2,3

1Physical Sciences for Health Doctoral Training Centre, University of Birmingham, Birmingham, United Kingdom, 2Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom, 3Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom, 4School of Computer Science, University of Birmingham, Birmingham, United Kingdom

There is a need for a method that can detect the number of components within multi b-value diffusion-weighted imaging. In particular, this would aid in the identification and correction of partial volume effects (PVE) within the brain. A PVE model was simulated to contain varying ratios of cerebrospinal fluid and white matter. Multi-exponential fitting methods were applied and found to be unsuccessful in identifying the number of components within the model. A novel fitting method, the Autoregressive Discrete Acquisition Points Transformation, was applied to simulations. Following manipulation through the discrete Z-domain, the number of components were correctly identified.

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