Abstract
Image bias is a usual phenomenon in MR imaging when using surface coils. It complicates the interpretation as well as the algorithmic postprocessing of such data. We introduce a bias correction algorithm based on homomorphic unsharp masking (HUM) that is applicable on a broad range of image types (as long as fore- and background is separable), simple, fast and requires only minimal user interaction. The results of this new algorithm are superior to HUM, especially with regards to feature separability.
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Gaudnek, M. A., Hess, A., Obermayer, K., Sibila, M., Tolxdorff, T., Braun, J., … Gesellschaft für Informatik (GI). (2008). Bildverarbeitung für die Medizin 2008. (T. Tolxdorff, J. Braun, T. M. Deserno, A. Horsch, H. Handels, & H.-P. Meinzer, Eds.) (pp. 373–376). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-78640-5
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