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Proceedings Paper

Fast bias field reduction by localized Lloyd-Max quantization
Author(s): R. Hanel; K. J. Batenburg; S. De. De Backer; P. Scheunders; J. Sijbers
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Paper Abstract

Bias field reduction is a common problem in medical imaging. A bias field usually manifests itself as a smooth intensity variation across the image. The resulting image inhomogeneity is a severe problem for posterior image processing and analysis techniques such as registration or segmentation. In this paper, we present a fast debiasing technique based on localized Lloyd-Max quantization. Thereby, the local bias is modelled as a multiplicative field and is assumed to be slowly varying. The method is based on the assumption that the local, undegraded histogram is characterized by a limited number of gray values. The goal is then to find the discrete intensity values such that spreading those values according to the local bias field reproduces the global histogram as good as possible. We show that our method is capable of efficiently reducing (even strong) bias fields in 3D volumes in only a few seconds.

Paper Details

Date Published: 19 March 2008
PDF: 8 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69141A (19 March 2008); doi: 10.1117/12.770724
Show Author Affiliations
R. Hanel, Medical Univ. of Vienna (Austria)
Univ. of Antwerp (Belgium)
K. J. Batenburg, Univ. of Antwerp (Belgium)
S. De. De Backer, Univ. of Antwerp (Belgium)
P. Scheunders, Univ. of Antwerp (Belgium)
J. Sijbers, Univ. of Antwerp (Belgium)

Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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