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A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification

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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

This paper presents a general and unifying optimization framework for the problem of feature extraction and reduction for high-dimensional pattern classification of medical images. Feature extraction is often an ad hoc and case-specific task. Herein, we formulate it as a problem of sparse decomposition of images into a basis that is desired to possess several properties: 1) Sparsity and local spatial support, which usually provides good generalization ability on new samples, and lends itself to anatomically intuitive interpretations; 2) good discrimination ability, so that projection of images onto the optimal basis yields discriminant features to be used in a machine learning paradigm; 3) spatial smoothness and contiguity of the estimated basis functions. Our method yields a parts-based representation, which warranties that the image is decomposed into a number of positive regional projections. A non-negative matrix factorization scheme is used, and a numerical solution with proven convergence is used for solution. Results in classification of Alzheimers patients from the ADNI study are presented.

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Author information

Authors and Affiliations

  1. Section of Biomedical Image Analysis, Raddiology Department, University of Pennsylvania, Philadelphia, PA 19014, USA

    Nematollah Batmanghelich & Christos Davatzikos

  2. Computer and Information Department, University of Pennsylvania, Philadelphia, PA 19104, USA

    Ben Taskar

Authors
  1. Nematollah Batmanghelich
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  2. Ben Taskar
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  3. Christos Davatzikos
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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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Batmanghelich, N., Taskar, B., Davatzikos, C. (2009). A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification. 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_35

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  • DOI: https://doi.org/10.1007/978-3-642-02498-6_35

  • 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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