Meshes Meet Voxels: Abdominal Organ Segmentation via Diffeomorphic Deformations
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Abdominal multi-organ segmentation from CT and MRI is an essential prerequisite for surgical planning and computer-aided navigation systems. Three-dimensional numeric representations of abdominal shapes are further important for quantitative and statistical analyses thereof. Existing methods in the field, however, are unable to extract highly accurate 3D representations that are smooth, topologically correct, and match points on a template. In this work, we present UNetFlow, a novel diffeomorphic shape deformation approach for abdominal organs. UNetFlow combines the advantages of voxel-based and mesh-based approaches for 3D shape extraction. Our results demonstrate high accuracy with respect to manually annotated CT data and better topological correctness compared to previous methods. In addition, we show the generalization of UNetFlow to MRI.
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