Comparison of feature extraction methods for breast cancer detection

Authors:
Rafael Llobet;Roberto Paredes;Juan C. Pérez-Cortés
Affiliations:
Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Valencia, Spain;Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Valencia, Spain;Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Valencia, Spain
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

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Abstract

Although screening mammography is widely used for the detection of breast tumors, it is difficult for a radiologist to interpret correctly a mammogram. It is possible to improve this task by using a computer aided diagnosis system (CAD) which highlights the areas most likely to contain cancer cells. In this paper, we present and compare five different feature extraction methods for breast cancer detection in digitized mammograms. All the methods are based on features extracted from a local window and on a k-nearest neighbor classifier with fast search.