Choquet Integral based Feature Selection for Early Breast Cancer Diagnosis from MRIs

Soumaya Trabelsi Ben Ameur, Florence Cloppet, Dorra Sellami Masmoudi, Laurent Wendling

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 Harvard Style

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


in Bibtex Style

@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},
}


in EndNote Style

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