Abstract
Digital mammography and comprehensive breast cancer screening approaches have led to the generation of a vast amount of image data. Since the visual inspection of a large set of images is expensive and to some extend also subjective, new methods for fully automated mammography image analysis are needed. The Definiens Cognition Network Technology (CNT) solves the image analysis problem by simulating human cognition processes using knowledge based and context dependent processing. It represents processed image data, image processing methods, and image objects and their definitions in a unified model which incorporates elements from semantic networks, description logics and functional programming. We present first steps towards a successful application of this technology on automated detection of masses and calcifications according to the ACR BI-RADS™ standard.
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© 2007 Springer-Verlag Berlin Heidelberg
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Schmidt, G. et al. (2007). Cognition Network Technology for Automated Holistic Analysis in Mammography. In: Horsch, A., Deserno, T.M., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2007. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71091-2_57
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DOI: https://doi.org/10.1007/978-3-540-71091-2_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71090-5
Online ISBN: 978-3-540-71091-2
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