Multi-atlas automatic positioning of anatomical landmarks

We propose a method for the automatic positioning of pre-defined landmarks on 3-D models of anatomical structures. We exploit a group of atlases consisting of multiple triangular meshes for which the defined landmarks have been placed by experts. We compute an initial coarse global registration of the patient mesh with an expert mesh by using a curvature-enhanced Iterative Closest Point (ICP) algorithm. Adaptive local rigid registrations refine the fit for the projection of reference landmarks onto the surface of the patient structure. An automatic selection based on a fit criterion computes a final position for each landmark. Our positioning method improves the efficiency of the positioning task, being completely unsupervised and yielding results competitive with those of the manual positioning. We provide comparisons with previous works of the literature. The automatic positioning for each target structure is completely reproducible as opposed to manual positioning, affected by intra-operator variability.