[Automatic segmentation using atlases in head and neck cancers: Methodology]. / Outils de contourage, utilisation et construction d'atlas anatomiques : exemples des cancers de la tête et du cou.

Highly conformal irradiation techniques are associated with steep gradient doses. Accuracy and reproducibility of delineation are required to avoid geometric misses and to properly report dose-volume effects on organs at risk. Guidelines of the International Commission on Radiation Units have largely contributed to high quality treatments. The ICRU endeavors to collect and evaluate the latest data and information pertinent to the problems of radiation measurement and dosimetry. There remains a need for delineation guidelines and automatic segmentation tools in routine practice. Among these tools, atlas-based segmentation has been shown to provide promising results. The methodology used for head and neck cancer patients is illustrated.

An efficient locally affine framework for the smooth registration of anatomical structures.

Intra-subject and inter-subject nonlinear registration based on dense transformations requires the setting of many parameters, mainly for regularization. This task is a major issue, as the global quality of the registration will depend on it. Setting these parameters is, however, very hard, and they may have to be tuned for each patient when processing data acquired by different centers or using different protocols. Thus, we present in this article a method to introduce more coherence in the registration by using fewer degrees of freedom than with a dense registration. This is done by registering the images only on user-defined areas, using a set of affine transformations, which are optimized together in a very efficient manner. Our framework also ensures a smooth and coherent transformation thanks to a new regularization of the affine components. Finally, we ensure an invertible transformation thanks to the Log-Euclidean polyaffine framework. This allows us to get a more robust and very efficient registration method, while obtaining good results as explained below. We performed a qualitative and quantitative evaluation of the obtained results on two applications: first on atlas-based brain segmentation, comparing our results with a dense registration algorithm. Then the second application for which our framework is particularly well suited concerns bone registration in the lower-abdomen area. We obtain in this case a better positioning of the femoral heads than with a dense registration. For both applications, we show a significant improvement in computation time, which is crucial for clinical applications.