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Authors: Rafael Llobet 1 ; Juan A. Solves 1 ; Juan C. Perez-Cortes 1 and Francisco Ruiz-Perales 2

Affiliations: 1 Universidad Politécnica de Valencia, Spain ; 2 Consellería de Sanitat. Comunitat Valenciana, Spain

Abstract: In this work, the task of classifying mammograms according to breast density is studied using a local-histogram-based feature extraction method and a non-parametric classification scheme. Breast density estimation is important due to its association with a higher risk of cancer and an increased difficulty of diagnosis. 322 images from the Mammographic Image Analysis Society (MIAS) Database have been analyzed, and the density prediction accuracy of the method has been assessed. The obtained results show an agreement of 77.96% between automatic and expert radiologist manual classification.

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Paper citation in several formats:
Llobet, R.; Solves, J.; Perez-Cortes, J. and Ruiz-Perales, F. (2009). Mammographic Density Classification based on Local Histograms. In Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems (BIOSTEC 2009) - Workshop MIAD; ISBN 978-989-8111-77-7, SciTePress, pages 85-90. DOI: 10.5220/0001813600850090

@conference{workshop miad09,
author={Rafael Llobet. and Juan A. Solves. and Juan C. Perez{-}Cortes. and Francisco Ruiz{-}Perales.},
title={Mammographic Density Classification based on Local Histograms},
booktitle={Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems (BIOSTEC 2009) - Workshop MIAD},
year={2009},
pages={85-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001813600850090},
isbn={978-989-8111-77-7},
}

TY - CONF

JO - Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems (BIOSTEC 2009) - Workshop MIAD
TI - Mammographic Density Classification based on Local Histograms
SN - 978-989-8111-77-7
AU - Llobet, R.
AU - Solves, J.
AU - Perez-Cortes, J.
AU - Ruiz-Perales, F.
PY - 2009
SP - 85
EP - 90
DO - 10.5220/0001813600850090
PB - SciTePress

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