Anisotropic adapted meshes for image segmentation: application to 3D medical data
Tuesday 21st July 2020
Clerici, F.; Ferro, N.; Marconi, S.; Micheletti, S.; Negrello, E.; Perotto, S.
This work focuses on a variational approach to image segmentation based on the Ambrosio-Tortorelli functional. We propose an efficient algorithm, which combines the functional minimization with a smart choice of the computational mesh. With this aim, we resort to an anisotropic mesh adaptation procedure driven by an a posteriori recovery-based error analysis. We apply the proposed algorithm to a Computed Tomography dataset of a fractured pelvis, to create a virtual model of the anatomy. The result is verified against a semi-automatic segmentation carried out using the ITK-SNAP tool. Furthermore, a physical replica of the virtual model is produced by means of Fused Filament Fabrication technology, to assess the appropriateness of the proposed solution in terms of resolution-quality balance for 3D printing production.