ABC in Nuclear Imaging

TL;DR

This paper explores the use of approximate Bayesian Computation (ABC) for parameter estimation in PET nuclear imaging, demonstrating its effectiveness on a neurotransmitter response model and comparing it with existing methods.

Contribution

It introduces a simple ABC algorithm tailored for compartmental model parameter estimation in PET imaging, filling a gap in current methodologies.

Findings

ABC provides accurate parameter estimates in PET models

The proposed method outperforms some existing approaches

Demonstrated on neurotransmitter response data

Abstract

We consider the application of approximate Bayesian Computation (ABC) in the context of medical imaging data. We consider the parameter estimation of compartmental models in PET imaging analysis, and provide a simple ABC algorithm for its estimation. We demonstrate the utility of the proposed estimation methods on a neurotransmitter response model, and compare our approach to existing methods.