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IJAIT
2006

An Efficient Feature Selection Algorithm for Computer-aided Polyp Detection

11 years 9 months ago
An Efficient Feature Selection Algorithm for Computer-aided Polyp Detection
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).
Jiang Li, Jianhua Yao, Ronald M. Summers, Nicholas
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where IJAIT
Authors Jiang Li, Jianhua Yao, Ronald M. Summers, Nicholas Petrick, Michael T. Manry, Amy K. Hara
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