"Joint Intensity Inhomogeneity Correction for Whole-Body MR Data"

Oleh Dzyubachyk, Rob J. van der Geest, Marius Staring, Peter Börnert, Monique Reijnierse, Johan L. Bloem and Boudewijn P.F. Lelieveldt


Whole-body MR receives increasing interest as potential alternative to many conventional diagnostic methods. Typical whole-body MR scans contain multiple data channels and are acquired in a multistation manner. Quantification of such data typically requires correction of two types of artefacts: different intensity scaling on each acquired image stack, and intensity inhomogeneity (bias) within each stack. In this work, we present an all-in-one method that is able to correct for both mentioned types of acquisition artefacts. The most important properties of our method are: 1) All the processing is performed jointly on all available data channels, which is necessary for preserving the relation between them, and 2) It allows easy incorporation of additional knowledge for estimation of the bias field. Performed validation on two types of whole-body MR data confirmed superior performance of our approach in comparison with state-of-the-art bias removal methods.



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Copyright © 2013 by the authors. Published version © 2013 by Springer Lecture Notes in Computer Science. Personal use of this material is permitted. However, permission to reprint or republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the copyright holder.


BibTeX entry

author = "{Oleh Dzyubachyk and Rob J. van der Geest and Marius Staring and Peter Börnert and Monique Reijnierse and Johan L. Bloem and Boudewijn P.F. Lelieveldt}",
title = "{Joint Intensity Inhomogeneity Correction for Whole-Body MR Data}",
booktitle = "{Medical Image Computing and Computer-Assisted Intervention}",
editor = "{K. Mori and I. Sakuma and Y. Sato and C. Barillot and N. Navab}",
address = "{Nagoya, Japan}",
series = "{Lecture Notes in Computer Science}",
volume = "{8149}",
pages = "{106 - 113}",
month = "{September}",
year = "{2013}",

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