Abstract
One of the key problems in magnetic resonance (MR) image analysis is to remove the intensity inhomogeneity artifact present in MR images, which often degrades the performance of an automatic image analysis technique. In this regard, the paper presents a novel approach for bias field correction in MR images using the merit of contraharmonic mean, which is used in low-pass averaging filter to estimate the near optimum bias field in multiplicative model. A theoretical analysis is presented to justify the use of contraharmonic mean for bias field estimation. The performance of the proposed approach, along with a comparison with other bias field correction algorithms, is demonstrated on a set of MR images for different bias fields and noise levels.
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Banerjee, A., Maji, P. (2013). Contraharmonic Mean Based Bias Field Correction in MR Images. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_63
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DOI: https://doi.org/10.1007/978-3-642-40261-6_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40260-9
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