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arXiv · 2406.12407

LOOC: Localizing Organs using Occupancy Networks and Body Surface Depth Images

Pit Henrich·Franziska Mathis-Ullrich
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Abstract

We introduce a novel approach for the precise localization of 67 anatomical structures from single depth images captured from the exterior of the human body. Our method uses a multi-class occupancy network, trained using segmented CT scans augmented with body-pose changes, and incorporates a specialized sampling strategy to handle densely packed internal organs. Our contributions include the application of occupancy networks for occluded structure localization, a robust method for estimating anatomical positions from depth images, and the creation of detailed, individualized 3D anatomical atlases. We outperform localization using template matching and provide qualitative real-world reconstructions. This method promises improvements in automated medical imaging and diagnostic procedures by offering accurate, non-invasive localization of critical anatomical structures.

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Pit Henrich, Franziska Mathis-Ullrich. 2024-06-18. LOOC: Localizing Organs using Occupancy Networks and Body Surface Depth Images. https://doi.org/10.1109/access.2025.3543736

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