Abstract
The article presents the abnormal textures identification technology based on structural and statistical models of amplitude-phase images (APIm) – multidimensional data arrays (semantic models) and statistical correlation analysis methods using the generalized discrete Hilbert transforms (DHT) – 2D Hilbert (Foucault) isotropic (HTI), anisotropic (HTA) and total transforms – AP-analysis (APA) to calculate the APIm. The identified fragments of textures are obtained as examples of experimental observation of real mammograms contains areas of pathological tissues. The DHT based information technology as conceptual chart description is discussed and illustrated with DHO domain images. As additional method for anomaly of tissue detecting the multiply cascade DHT is proposed and elaborated at base transforms domains. The enhancement of abnormal texture areas at mammograms processed could increase the abilities of identification methodic and diagnostic systems.
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Vlasenko, V., Stemplewski, S., Koczur, P. (2018). Abnormal Textures Identification Based on Digital Hilbert Optics Methods: Fundamental Transforms and Models. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017. ISAT 2017. Advances in Intelligent Systems and Computing, vol 656. Springer, Cham. https://doi.org/10.1007/978-3-319-67229-8_7
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DOI: https://doi.org/10.1007/978-3-319-67229-8_7
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