Mixture Prior Distributions and Bayesian Models for Robust Radionuclide Image Processing

Zhang, M., Aykroyd, R.G. and Tsoumpas, C. (2024) Mixture Prior Distributions and Bayesian Models for Robust Radionuclide Image Processing. Frontiers in Nuclear Medicine, 4. ISSN 2673-8880

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Zhang, M.
  • Aykroyd, R.G.
  • Tsoumpas, C.
Copyright, Publisher and Additional Information:

© 2024 Zhang, Aykroyd and Tsoumpas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Keywords: medical imaging, Bayesian methods, machine learning, Inhomogeneous models, Markov chain Monte Carlo
Dates:
  • Published: 5 September 2024
  • Published (online): 5 September 2024
  • Accepted: 13 August 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 05 Sep 2024 11:13
Last Modified: 16 Sep 2024 12:01
Published Version: https://www.frontiersin.org/journals/nuclear-medic...
Status: Published
Publisher: Frontiers Media
Identification Number: 10.3389/fnume.2024.1380518
Open Archives Initiative ID (OAI ID):

Export

Statistics