NDLI: Exploring Ranklets Performances in Mammographic Mass Classification using Recursive Feature Elimination

Content Provider	IEEE Xplore Digital Library
Author	Masotti, M.
Copyright Year	2006
Description	Author affiliation: Dept. of Phys., Univ. of Bologna, Bologna (Masotti, M.)
Abstract	The ranklet transform is a recently developed image processing technique characterized by a multi-resolution and orientation-selective approach similar to that of the wavelet transform. Yet, differently from the latter, it deals with pixels' ranks rather than with their gray-level intensity values. In this work, the ranklet coefficients resulting from the application of the ranklet transform to regions of interest (ROIs) found on breast radiographic images are used as classification features to determine whether ROIs contain mass or normal tissue. Performances are explored recursively eliminating some of the less discriminant ranklet coefficients according to the cost function of a support vector machine (SVM) classifier. Experiments show good classification performances $(A_{z}$ values of 0.976 plusmn 0.003) even after a significant reduction of the number of ranklet coefficients.
Starting Page	265
Ending Page	270
File Size	6520632
Page Count	6
File Format	PDF
ISBN	1424406560
ISSN	15512541
DOI	10.1109/MLSP.2006.275559
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-09-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine classification Wavelet transforms Image databases Breast Diagnostic radiography Spatial databases Face detection Delta-sigma modulation Physics
Content Type	Text
Resource Type	Article

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