A general and unifying framework for feature construction, in image-based pattern classification

Nematollah Batmanghelich, Ben Taskar, Christos Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationInformation Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings
Pages423-434
Number of pages12
DOIs
StatePublished - Sep 21 2009
Event21st International Conference on Information Processing in Medical Imaging, IPMI 2009 - Williamsburg, VA, United States
Duration: Jul 5 2009Jul 10 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5636 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Conference on Information Processing in Medical Imaging, IPMI 2009
CountryUnited States
CityWilliamsburg, VA
Period7/5/097/10/09

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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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 Information Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings (pp. 423-434). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5636 LNCS). https://doi.org/10.1007/978-3-642-02498-6_35