Amina Salhi

Abstract The characterization of brain tumors from magnetic resonance imaging (MRI) is crucial for diagnosis, treatment planning, and prognosis. But the analysis of brain tumors based on MRI is still difficult because of the significant intra-tumoral heterogeneity, ambiguous boundaries of lesions, high dimensionality of imaging features, and complicated nonlinear relationships between anatomical structures.

ABSTRACT Heterogeneous change detection is concerned with identifying surface changes based on multi-temporal remote sensing images, taken using a variety of sensors. The main problem lies in the fact that one has to reconcile non-linear radiometric differences and modality-specific distortions in order to maintain semantic consistency.

Abstract The long-term physiologic effects of thyroid problems make them one of the most important endocrine disorders. Even if a lot of machine learning and deep learning techniques have been presented out for the early detection of thyroid disease, it is still difficult to achieve reliable and clinically accurate multi-class diagnostic performance.