Abstract
3D reconstruction and digital double staining offer pathologists many new insights into tissue structure and metabolism. Key to these applications is the precise registration of histological slide images, that is challenging in several ways. One major challenge are differently stained slides, that highlight different parts of the tissue. In this paper we introduce a new registration method to face this multimodality. It abstracts the image information to cell nuclei densities. By minimizing the distance of these densities an affine transformation is determined that restores the lost spatial correspondences. The proposed density based registration is evaluated using consecutive histological slides. It is compared to a Mutual Information based registration and shown to be more accurate and robust.
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Weiss, N., Lotz, J., Modersitzki, J. (2015). Multimodal Image Registration in Digital Pathology Using Cell Nuclei Densities. 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_43
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DOI: https://doi.org/10.1007/978-3-662-46224-9_43
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