Anisotropic adapted meshes for image segmentation: application to 3D medical data
Keywords
Advanced Numerical Methods for Scientific Computing
Computational Medicine for the Cardiocirculatory System
Code:
48/2020
Title:
Anisotropic adapted meshes for image segmentation: application to 3D medical data
Date:
Tuesday 21st July 2020
Author(s):
Clerici, F.; Ferro, N.; Marconi, S.; Micheletti, S.; Negrello, E.; Perotto, S.
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Abstract:
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 veri fied 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.