Abstract
The Apparent Diffusion Coefficient (ADC) is often considered in the differential diagnosis of tumors, since the analysis of a field of ADCs on a particular region of the body allows to identify regional necrosis. This quantity can be estimated from magnitude signals obtained in diffusion Magnetic Resonance (MR), but in some situations, like total body MRs, it is possible to repeat only few measurements on the same patient, thus providing a limited amount of data for the estimation of ADCs. In this work we consider a Rician distributed magnitude signal with an exponential dependence on the so-called b-value. Different pixelwise estimators for the ADC, both frequentist and Bayesian, are proposed and compared by a simulation study, focusing on issues caused by low signal-to-noise ratios and small sample sizes.
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Baraldo, S., Ieva, F., Mainardi, L., Paganoni, A.M. (2013). Estimation Approaches for the Apparent Diffusion Coefficient in Rice-Distributed MR Signals. In: Grigoletto, M., Lisi, F., Petrone, S. (eds) Complex Models and Computational Methods in Statistics. Contributions to Statistics. Springer, Milano. https://doi.org/10.1007/978-88-470-2871-5_2
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DOI: https://doi.org/10.1007/978-88-470-2871-5_2
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