The goal of this thesis is to provide automatic segmentation tools based on the use of anatomical atlases. The proposed algorithms are applied and evaluated in the context of radiotherapy of head and neck cancers : segmentation of the organs at risk and the lymph node levels of the neck for treatment planning, and segmentation of the teeth to assess the risk level associated to a given post-irradiation dental care. We first address the construction of an average atlas from a database of manually delineated images considered as reference atlases. In particular, we propose several algorithms to estimate an average segmentation from incomplete segmentations that comprise of missing contours. In order to get over the limits inherent in the average atlas, and in particular its di culty to cope with the inter-individual anatomical variability, we propose to build several average atlases after strati fication of the database into several sub-groups, and to use for each patient the most appropriate average atlas. Then, we present several approaches to select and fuse the most relevant atlases of the database for each patient. We propose global, regional, and local approaches for atlas selection, and an unbiaised protocol to assess them. We also propose several methods for the atlas fusion step, and in particular the construction of a patient-specifi c average atlas from the most similar atlases selected on each region. We show that the selection and fusion of atlases enable a signi ficant improvement compared to the use of the average atlas. Most of this work was integrated into the software ISOgray commercialised by DOSIsoft.
