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Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum

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Spectral and Shape Analysis in Medical Imaging (SeSAMI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10126))

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Abstract

The Corpus Callosum (CC) has been a structure of much interest in neuroimaging studies of normal brain development, schizophrenia, autism, bipolar and unipolar disorder. In this paper, we present a technique which allows us to develop a shape preservation methodology in the deformation of CC for further global and regional shape analyzes between two sample corpora callosa. Source and target CC are superpositioned individually from eleven anchor points. Source CC is deformed in order to get superpositioned onto the target CC from these anchor points and superposition operation leads other anatomical landmarks to get placed automatically in all of the regions of source CC for further deformation analysis. Region construction via quadratic Bézier curves, deformation by using Gaussian RBF and quantifying the amount of deformation via generalized Procrustes analysis are used to infer the proper parameters used in minimum deformation. Amount of deformation can be analyzed both regionally and globally.

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Author information

Authors and Affiliations

  1. Informatics Institute, METU, Ankara, Turkey

    Umut Orcun Turgut & Didem Gokcay

Authors
  1. Umut Orcun Turgut
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  2. Didem Gokcay
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Corresponding author

Correspondence to Umut Orcun Turgut .

Editor information

Editors and Affiliations

  1. Harvard Medical School, Boston, Massachusetts, USA

    Martin Reuter

  2. Ludwig-Maximilian University of Munich, Munich, Germany

    Christian Wachinger

  3. Inria Sophia Antipolis, Sophia Antipolis, France

    Hervé Lombaert

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© 2016 Springer International Publishing AG

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Turgut, U.O., Gokcay, D. (2016). Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum. In: Reuter, M., Wachinger, C., Lombaert, H. (eds) Spectral and Shape Analysis in Medical Imaging. SeSAMI 2016. Lecture Notes in Computer Science(), vol 10126. Springer, Cham. https://doi.org/10.1007/978-3-319-51237-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-51237-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51236-5

  • Online ISBN: 978-3-319-51237-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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