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Cognitive Methods for Semantic Image Analysis in Medical Imaging Applications

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Natural User Interfaces in Medical Image Analysis

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

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Abstract

In the first part of this chapter will be briefly presented the foundations of selected imaging techniques making use of computed tomography (CT). It will be focused on dynamic CT perfusion (CTP) and computed tomography angiography (CTA). Computed tomography perfusion makes it possible to visualize structural, dynamic, and functional irregularities caused by ischemia, unlike CT which only shows static images of a patient’s tissues. In neuroradiography, perfusion image analysis is currently used in cases of head injuries, epilepsy, vascular brain diseases, and especially to diagnose strokes and brain tumors. Later, it will discuss some fundamentals of cognitive computer image analysis aimed at computer-aided diagnosis and semantic image description. The idea behind the semantic analysis of images is based on the resonance processes. It defines the cognitive resonance model and the methods of its implementation using image languages. The possibilities of conducting a semantic analysis are illustrated with medical samples of diagnostic images showing brain perfusion maps and computer 3-D reconstructions of carotid vessels.

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Authors and Affiliations

  1. AGH University of Science and Technology, Kraków, Poland

    Marek R. Ogiela

  2. Pedagogical University of Kraków, Kraków, Poland

    Tomasz Hachaj

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  1. Marek R. Ogiela
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  2. Tomasz Hachaj
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Correspondence to Marek R. Ogiela .

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Ogiela, M.R., Hachaj, T. (2015). Cognitive Methods for Semantic Image Analysis in Medical Imaging Applications. In: Natural User Interfaces in Medical Image Analysis. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-07800-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-07800-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07799-4

  • Online ISBN: 978-3-319-07800-7

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