Abstract
Although N3 is perhaps the most widely used method for MRI bias field correction, its underlying mechanism is in fact not well understood. Specifically, the method relies on a relatively heuristic recipe of alternating iterative steps that does not optimize any particular objective function. In this paper we explain the successful bias field correction properties of N3 by showing that it implicitly uses the same generative models and computational strategies as expectation maximization (EM) based bias field correction methods. We demonstrate experimentally that purely EM-based methods are capable of producing bias field correction results comparable to those of N3 in less computation time.
Original language | English |
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Title of host publication | Bayesian and Graphical Models for Biomedical Imaging : Revised Selected Papers of the first International Workshop on Bayesian and Grahical Models for Biomedical Imaging, BAMBI 2014 |
Publisher | Springer |
Publication date | 2014 |
Pages | 1-12 |
ISBN (Print) | 978-3-319-12288-5 |
ISBN (Electronic) | 978-3-319-12289-2 |
DOIs | |
Publication status | Published - 2014 |
Event | 1st International Workshop on Bayesian and Graphical Models for Biomedical Imaging, BAMBI 2014 - Cambridge, United States Duration: 18 Sept 2014 → … Conference number: 1 http://bambi.cs.ucl.ac.uk/ |
Workshop
Workshop | 1st International Workshop on Bayesian and Graphical Models for Biomedical Imaging, BAMBI 2014 |
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Number | 1 |
Country/Territory | United States |
City | Cambridge |
Period | 18/09/2014 → … |
Other | In correlation with the 17th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) |
Internet address |
Series | Lecture Notes in Computer Science |
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Number | 8677 |
ISSN | 0302-9743 |