Bayesian Nonparametrics and Biostatistics: The Case of PET Imaging

Fall Mame Diarra ()
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Fall Mame Diarra: Laboratoire de mathematiques analyse probabilites modelisation d’Orleans, Orleans45067, France

The International Journal of Biostatistics, 2019, vol. 15, issue 2, 10

Abstract: Biostatistic applications often require to collect and analyze a massive amount of data. Hence, it has become necessary to consider new statistical paradigms that perform well in characterizing complex data. Nonparametric Bayesian methods provide a widely used framework that offers the key advantages of a fully model-based probabilistic framework, while being highly flexible and adaptable. The goal of this paper is to provide a motivation of Bayesian nonparametrics (BNP) through a particular biomedical application, namely Positron Emission Tomography (PET) imaging reconstruction.

Keywords: Bayesian nonparametric; PET imaging; inverse problems; Markov Chain Monte Carlo (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1515/ijb-2017-0099

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