Automated recognition of cellular phenotypes by support vector machines with feature reduction

Y. Mao, Z. Xia, D. Pi, X. Zhou, Y. Sun, S. T C Wong

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

1 Scopus citations

Abstract

In this paper, wrapper based feature selection by support vector machine is used for cellular multi-phenotypic mitotic analysis (MMA) in high content screening (HCS). Haralick texture feature subset and Zernike polynomial moment subset are used respectively or combined together as extracted digital feature set for original cellular images. Feature reduction is done by support vector machine based recursive feature elimination algorithm on these feature sets. With optimal feature subset selected, fuzzy support vector machine are adopted to judge the cellular phenotype. The results indicate Haralick texture feature subset is complementary with Zernike polynomial moment subset, when these two feature subsets are combined together; the cellular phase identification system achieved 99.17% accuracy, which is better than only one feature subset of them is used. The recognition accuracy with feature reduction is better than that achieved when no feature reduction done or using PCA as feature recombination tool on these datasets.

Original languageEnglish (US)
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings
PublisherSpringer-Verlag
Pages171-178
Number of pages8
ISBN (Print)3540465359, 9783540465355
DOIs
StatePublished - 2006
Event10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 - Bournemouth, United Kingdom
Duration: Oct 9 2006Oct 11 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4251 LNAI - I
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
CountryUnited Kingdom
CityBournemouth
Period10/9/0610/11/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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