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

Soumaya Trabelsi Ben Ameur (1, 2) , Florence Cloppet (1) , Sellami Dorra (2) , Laurent Wendling (1)

1 LIPADE - EA 2517 - Laboratoire d'Informatique Paris Descartes
2 ENIS - École Nationale d'Ingénieurs de Sfax | National School of Engineers of Sfax

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.

Mots clés: Breast cancer; computer aided diagnosis; mammography; ultrasound; MRI; dual-energy contrast-enhanced digital mammography; Choquet integral

Domaines: Informatique [cs]

Soumaya Trabelsi Ben Ameur, Florence Cloppet, Sellami Dorra, Laurent Wendling. Choquet Integral based Feature Selection for Early Breast Cancer Diagnosis from MRIs. ICPRAM, Feb 2016, Rome, Italy. pp.351 - 358, ⟨10.5220/0005754703510358⟩. ⟨hal-01391970⟩