Apprentissage des informations cliniques à partir d'images médicales

This lecture will focus on the convergence medical imaging and machine learning techniques for the discovery and quantification of clinically useful information from medical images: The first part of the lecture will describe machine learning techniques such a dictionary learning that can be used for image reconstruction, e.g. the acceleration of MR imaging. The second part will discuss model-based approaches that employ statistical as well as probabilistic approaches for segmentation. In particular, we will focus on atlas-based segmentation approaches that employ advanced machine learning approaches such as manifold learning and classifier fusion to improve the accuracy and robustness of the segmentation approaches.