An efficient feature selection algorithm for computer-aided polyp detection

Jiang Li, Jianghua Yao, Ronald M. Summers, Amy Hara

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

2 Scopus citations

Abstract

We present an efficient feature selection algorithm for computer aided detection (CAD) computed tomographic (CT) colonography. The algorithm 1) determines an appropriate piecewise linear network (PLN) model based on a learning theorem for the given data set, 2) applies the orthonormal least square (OLS) procedure to the PLN model utilizing a Modified Schmidt procedure, and 3) uses a floating search algorithm to select features that minimize the output variance. The undesirable "nesting effect" is prevented by the floating search approach, and the piecewise linear OLS procedure makes this algorithm very computationally efficient because the Modified Schmidt procedure only requires one data pass during the whole searching process. The selected features are compared to those selected by other methods, through cross-validation with a committee of support vector machines (SVMs).

Original languageEnglish (US)
Title of host publicationRecent Advances in Artifical Intelligence - Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005
EditorsI. Russell, Z. Markov
Pages381-386
Number of pages6
StatePublished - Dec 1 2005
EventRecent Advances in Artifical Intelligence - Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 - Clearwater Beach, FL, United States
Duration: May 15 2005May 17 2005

Publication series

NameProceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 - Recent Advances in Artifical Intelligence

Other

OtherRecent Advances in Artifical Intelligence - Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005
CountryUnited States
CityClearwater Beach, FL
Period5/15/055/17/05

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Li, J., Yao, J., Summers, R. M., & Hara, A. (2005). An efficient feature selection algorithm for computer-aided polyp detection. In I. Russell, & Z. Markov (Eds.), Recent Advances in Artifical Intelligence - Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 (pp. 381-386). (Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 - Recent Advances in Artifical Intelligence).