N3 Bias Field Correction Explained as a Bayesian Modeling Method

Christian Thode Larsen, Juan Eugenio Iglesias, Koen Van Leemput

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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 languageEnglish
Title of host publicationBayesian and Graphical Models for Biomedical Imaging : Revised Selected Papers of the first International Workshop on Bayesian and Grahical Models for Biomedical Imaging, BAMBI 2014
PublisherSpringer
Publication date2014
Pages1-12
ISBN (Print)978-3-319-12288-5
ISBN (Electronic) 978-3-319-12289-2
DOIs
Publication statusPublished - 2014
Event1st International Workshop on Bayesian and Graphical Models for Biomedical Imaging, BAMBI 2014 - Cambridge, United States
Duration: 18 Sep 2014 → …
Conference number: 1
http://bambi.cs.ucl.ac.uk/

Workshop

Workshop1st International Workshop on Bayesian and Graphical Models for Biomedical Imaging, BAMBI 2014
Number1
CountryUnited States
CityCambridge
Period18/09/2014 → …
OtherIn correlation with the 17th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
Internet address
SeriesLecture Notes in Computer Science
Number8677
ISSN0302-9743

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