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The Role of Sparse Data Representation in Semantic Image Understanding

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Computer Vision and Graphics (ICCVG 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6374))

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Abstract

This paper discusses a concept of computational understanding of medical images in a context of computer-aided diagnosis. Fundamental research purpose was improved diagnosis of the cases, formulated by human experts. Designed methods of soft computing with extremely important role of: a) semantically sparse data representation, b) determined specific information, formally and experimentally, and c) computational intelligence approach were adjusted to the challenges of image-based diagnosis. Formalized description of image representation procedures was completed with exemplary results of chosen applications, used to explain formulated concepts, to make them more pragmatic and assure diagnostic usefulness. Target pathology was ontologically described, characterized by as stable as possible patterns, numerically described using semantic descriptors in sparse representation. Adjusting of possible source pathology to computational map of target pathology was fundamental issue of considered procedures. Computational understanding means: a) putting together extracted and numerically described content, b) recognition of diagnostic meaning of content objects and their common significance, and c) verification by comparative analysis with all accessible information and knowledge sources (patient record, medical lexicons, the newest communications, reference databases, etc.).

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Author information

Authors and Affiliations

  1. Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Artur Przelaskowski

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  1. Artur Przelaskowski
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Editor information

Editors and Affiliations

  1. Polish-Japanese Institute of Information Technology, 86 Koszykowa St, 02-008, Warsaw, Poland

    Leonard Bolc

  2. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences, Nowoursynowska 159, 02-776, Warsaw, Poland

    Leszek J. Chmielewski

  4. Polish-Japanese Institute of Information Technology, 86 Koszykowa St, 02-008 Warsaw, konradw@pjwstk.edu.pl, The Silesian University of Technology, Institute of Computer Science, Akademicka 16, 44-100 Gliwice, Polan

    Konrad Wojciechowski

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Przelaskowski, A. (2010). The Role of Sparse Data Representation in Semantic Image Understanding. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15910-7_8

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  • DOI: https://doi.org/10.1007/978-3-642-15910-7_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15909-1

  • Online ISBN: 978-3-642-15910-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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