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Brain and Neck Visualization Techniques

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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

This chapter will be devoted to image processing, analyzing and recognizing algorithms for brain perfusion computed tomography (CTP) and neck angiography images (CTA). Both of those are popular medical imaging methods that are often used beside standard computed tomography (CT) in acute stroke imaging. Imaging of the carotid arteries is important for the evaluation of patients with an ischemic stroke or a Transient Ischemic Attack (TIA). At first it will be presented the automatic method for the detection and recognition of potential lesions in brain perfusion that can be localized with the help of CTP maps. The second part of this chapter contains different approaches for enhancing and segmenting vascular structures that are visualized with three-dimensional computed tomography angiography images. That includes vessel-enhancing filtering, region growing based algorithms and deformable contour based approaches. We will discuss and evaluate the nearly automatic (it requires minimal initial configuration from the operator) framework that enables the segmentation of the single vessel lumen. We will present the results of this framework evaluation on the CTA images of the carotid artery bifurcation region.

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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

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

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© 2015 Springer International Publishing Switzerland

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Ogiela, M.R., Hachaj, T. (2015). Brain and Neck Visualization Techniques. 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_4

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  • DOI: https://doi.org/10.1007/978-3-319-07800-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07799-4

  • Online ISBN: 978-3-319-07800-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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