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19 March 2008 Fast bias field reduction by localized Lloyd-Max quantization
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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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. Hanel, K. J. Batenburg, S. De. De Backer, P. Scheunders, and J. Sijbers "Fast bias field reduction by localized Lloyd-Max quantization", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69141A (19 March 2008);

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