Robust variational segmentation of 3D bone CT data with thin cartilage interfaces

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HighlightsA two-stage variational approach for segmenting 3D bone CT data is proposed.Well-separated regions are identified by a flux-augmented Chan–Vese model.A phase-field fracture inspired method is presented to remove fine-scale contacts.Accuracy, robustness and automation is demonstrated for 3D femur and vertebra.Graphical abstractWe present a two-stage variational approach for segmenting 3D bone CT data that performs robustly with respect to thin cartilage interfaces. In the first stage, we minimize a flux-augmented Chan–Vese model that accurately segments well-separated regions. In the second stage, we apply a new phase-field fracture inspired model that reliably eliminates spurious bridges across thin cartilage interfaces, resulting in an accurate segmentation topology, from which each bone object can be identified. Its mathematical formulation is based on the phase-field approach to variational fracture, which naturally blends with the variational approach to segmentation. We successfully test and validate our methodology for the segmentation of 3D femur and vertebra bones, which feature thin cartilage regions in the hip joint, the intervertebral disks, and synovial joints of the spinous processes. The major strength of the new methodology is its potential for full automation and seamless integration with downstream predictive bone simulation in a common finite element framework.

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