Using local extremum curvatures to extract anatomical markers from medical images

Among the studies concerning the segmentation and the identification of anatomical structures from medical images, one of the major problems is the fusion of heterogeneous data for the recognition of these structures. In this domain, the fusion of inter-patient data for the constitution of anatomical models for instance is particularly critical especially with regards to the identification of complex cerebral structures like the cortical gyri. The goal of this work is to find anatomical markers which can be useful to characterize specific regions in brain images by using either CT or MR images. We have focused this study on the definition of a geometrical operator based on the detection of local extremum curvatures. The main issues addressed by this work concern the fusion of multimodal data from one patient (e.g. between CT and MRI) and moreover the fusion of inter-patient data as a first step toward the modelling of brain morphological deformations. Examples are shown upon 2D MR and CT brain images.