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Model-based Recognition of anatomical objects from medical images

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Information Processing in Medical Imaging (IPMI 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 687))

Abstract

We present both a high-level symbolic model of the human brain, and a method of using this model to aid in the recognition of objects from medical images. The model is stored as a frame based semantic network consisting of three coexisting graphs (a spatial adjacency graph; a part hierarchy; and an inheritance graph). We propose a method similar to assumption-based truth maintenance systems for the collating and reasoning processes required in the labelling of input images.

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Author information

Authors and Affiliations

  1. Dept of Neurology, UMDS (Guy's Hospital), SE1 9RT, London

    Glynn P. Robinson, Alan C. F. Colchester & Lewis D. Griffin

Authors
  1. Glynn P. Robinson
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  2. Alan C. F. Colchester
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  3. Lewis D. Griffin
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Editor information

Harrison H. Barrett A. F. Gmitro

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© 1993 Springer-Verlag Berlin Heidelberg

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Robinson, G.P., Colchester, A.C.F., Griffin, L.D. (1993). Model-based Recognition of anatomical objects from medical images. In: Barrett, H.H., Gmitro, A.F. (eds) Information Processing in Medical Imaging. IPMI 1993. Lecture Notes in Computer Science, vol 687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0013789

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  • DOI: https://doi.org/10.1007/BFb0013789

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56800-1

  • Online ISBN: 978-3-540-47742-6

  • eBook Packages: Springer Book Archive

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