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Authors: Soumaya Trabelsi Ben Ameur 1 ; Florence Cloppet 2 ; Dorra Sellami Masmoudi 3 and Laurent Wendling 2

Affiliations: 1 Paris Descartes University and National Engineering School of Sfax (ENIS), France ; 2 Paris Descartes University, France ; 3 National Engineering School of Sfax (ENIS), Tunisia

ISBN: 978-989-758-173-1

Keyword(s): Breast Cancer, Computer Aided Diagnosis, Mammography, Ultrasound, MRI, Dual-energy Contrast-Enhanced Digital Mammography, Choquet Integral.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Classification ; Clustering ; Computational Intelligence ; Feature Selection and Extraction ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Object Recognition ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Software Engineering ; Theory and Methods

Abstract: This paper focuses on breast cancer of the mammary gland. Both basic segmentation steps and usual features are recalled. Then textural and morphological information are combined to improve the overall performance of breast MRI in a computer-aided system. A model of selection based on Choquet integral is provided. Such model is suitable when handling with a weak amount of data even ambiguous in some extent. Achieved results compared to well-known classification methods show the interest of our approach.

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Paper citation in several formats:
Trabelsi Ben Ameur, S.; Cloppet, F.; Sellami Masmoudi, D. and Wendling, L. (2016). Choquet Integral based Feature Selection for Early Breast Cancer Diagnosis from MRIs.In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 351-358. DOI: 10.5220/0005754703510358

@conference{icpram16,
author={Soumaya Trabelsi Ben Ameur. and Florence Cloppet. and Dorra Sellami Masmoudi. and Laurent Wendling.},
title={Choquet Integral based Feature Selection for Early Breast Cancer Diagnosis from MRIs},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={351-358},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005754703510358},
isbn={978-989-758-173-1},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Choquet Integral based Feature Selection for Early Breast Cancer Diagnosis from MRIs
SN - 978-989-758-173-1
AU - Trabelsi Ben Ameur, S.
AU - Cloppet, F.
AU - Sellami Masmoudi, D.
AU - Wendling, L.
PY - 2016
SP - 351
EP - 358
DO - 10.5220/0005754703510358

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