The investigation of uncertainty is of major importance in risk-critical applications, such as
medical image segmentation. Belief function theory, a formal framework for uncertainty …

Accurate breast region segmentation is an important step in various automated algorithms
involving detection of lesions like masses and microcalcifications, and efficient …

Artificial intelligence algorithms, specifically deep learning, can assist radiologists by
automating mammogram density assessment. However, trust in such algorithms must be …

Deep learning has shown promising contributions in medical image segmentation with
powerful learning and feature representation abilities. However, it has limitations for …

Based on the review and survey I will get a way out to analyze breast cancer in a more
precise manner at the initial stage itself by using mammogram images. Initially, pre …

Le raisonnement est un «processus cognitif» qui permet de lier, au moyen de règles
logiques ou conventionnelles, deux ou plusieurs propositions pour en tirer une conclusion …

In this study, we present an evidential deep learning framework called MV-DEFEAT,
incorporating the strength of Dempster-Shafer evidential theory and subjective logic, for …

The fruit of this thesis would not have been possible to see light without the support of many
people. Many thanks to my adviser, Pr. Hayet Farida Merouani, who was there, with helping …