Nonlinear Smoothing of MR Images Using Approximate Entropy - A Local Measure of Signal Intensity Irregularity

Authors:
Geoffrey J. M. Parker;Julia A. Schnabel;Gareth J. Barker
Affiliations:
-;-;-
Venue:
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Year:
1999

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Abstract

Approximate entropy (ApEn) is a computable measure of sequential irregularity that is applicable to sequences of numbers of finite length. As such, it may be used to determine how random a sequence of numbers is. We exploit this property to determine the relevance of image information; to determine whether a spatial signal intensity distribution varies in a regular fashion -- and is therefore likely to be an image feature or image texture, or is highly random -- and likely to be noise. We present an outline of two possible methodologies for creating an ApEn-based noise filter: a modified median filter and a modified anisotropic diffusion scheme. We show that both approaches lead to effective noise reduction in MR images, with improved information-retaining properties when compared with their conventional counterparts.