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Abstract #2361

Getting more from less: a morphological model of diffusion in the prostate for improving the predictive power of DWI in identifying tumors.

David Willis1, Donnie Cameron1, Paul Malcolm2, and Glyn Johnson1

1Norwich Medical School, University of East Anglia, Norwich, NR4 7UQ, UK, United Kingdom, 2Department of Radiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom

We constructed a morphological model of diffusion in the prostate from a limited number of diffusion-weighted images to increase the sensitivity of such diffusion imaging to the presence of prostate cancer. Estimating the measurement error (9.9%) and characterizing the prostate from a large public dataset (n=206) has shown morphological relationships (|r|>0.5) and provided distributions and relationships within the available ADC measures. A model can then be used to give expected values to test against, and enable much larger datasets to be synthesized with the aim of testing various machine learning approaches.

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