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Automatic Segmentation of Brain Structures Using Geometric Moment Invariants and Artificial Neural Networks

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Information Processing in Medical Imaging (IPMI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5636))

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Abstract

We propose an automatic method for the segmentation of the brain structures in three dimensional (3D) Magnetic Resonance Images (MRI). The proposed method consists of two stages. In the first stage, we represent the shape of the structure using Geometric Moment Invariants (GMIs) in 8 scales. For each scale, an Artificial Neural Network (ANN) is designed to approximate the signed distance function of a desired structure. The GMIs along with the voxel intensities and coordinates are used as the input features of the ANN and the signed distance function as its output. In the second stage, we combine the outputs of the ANNs of the first stage and design another ANN to classify the image voxels into two classes, inside or outside of the structure. We introduce a fast method for moment calculations. The proposed method is applied to the segmentation of caudate, putamen, and thalamus in MRI where it has outperformed other methods in the literature.

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Author information

Authors and Affiliations

  1. Control and Intelligent Processing Center of Excellence, Department of Electrical and Computer Engineering, University of Tehran, Tehran, Iran

    Mostafa Jabarouti Moghaddam & Hamid Soltanian-Zadeh

  2. Image Analysis Laboratory, Department of Radiology, Henry Ford Hospital, Detroit, Michigan, USA

    Hamid Soltanian-Zadeh

Authors
  1. Mostafa Jabarouti Moghaddam
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  2. Hamid Soltanian-Zadeh
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 North Charles Street, MD 21218, Baltimore, USA

    Jerry L. Prince

  2. Department of Radiology, Johns Hopkins University, 600 North Wolfe Street, MD 21287, Baltimore, USA

    Dzung L. Pham

  3. Division of Imaging and Applied Mathematics, OSEL, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, MD 20993, Silver Spring, USA

    Kyle J. Myers

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© 2009 Springer-Verlag Berlin Heidelberg

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Jabarouti Moghaddam, M., Soltanian-Zadeh, H. (2009). Automatic Segmentation of Brain Structures Using Geometric Moment Invariants and Artificial Neural Networks. In: Prince, J.L., Pham, D.L., Myers, K.J. (eds) Information Processing in Medical Imaging. IPMI 2009. Lecture Notes in Computer Science, vol 5636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02498-6_27

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  • DOI: https://doi.org/10.1007/978-3-642-02498-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02497-9

  • Online ISBN: 978-3-642-02498-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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