Abstract
Image registration is particularly challenging if the images to be aligned contain non-corresponding regions. Using state-of-the-art algorithms typically leads to unwanted and unrealistic deformations in these regions. There are various approaches handling this problem which improve registration results, however each with a focus on specific applications. In this note we describe a general approach which can be applied on different mono-modal registration problems. We show the effects of this approach compared to a standard registration algorithm on the basis of five 3D CT lung image pairs where synthetic tumors have been added. We show that our approach significantly reduces unwanted deformation of a non-corresponding tumor. The average volume decrease is 9% compared to 66% for the standard approach while the overall accuracy based on landmark error is retained.
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Drobny, D., Carolus, H., Kabus, S., Modersitzki, J. (2015). Handling Non-Corresponding Regions in Image Registration. In: Handels, H., Deserno, T., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2015. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46224-9_20
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DOI: https://doi.org/10.1007/978-3-662-46224-9_20
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