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Department of Quantitative Biomedicine

The Menze group develops a deep neural network to reconstruct the 3D standing spine posture from 2D Radiographs

Anatomy-Aware Inference of the 3D Standing Spine Posture from 2D Radiographs

In various spinal disorders, a biomechanical load analysis of the spine in the upright position is useful to understand the underlying causes of the disorder and to help guide therapy. Despite the complex 3D shape of the human spine, this analysis is typically performed using 2D radiographs. Here, the Menze group proposes a novel deep neural network architecture, which takes orthogonal 2D radiographs and infers the spine’s 3D posture using vertebral shape priors to reconstruct the 3D spinal pose in an upright standing position.

See Bayat et al., Tomography


Fig.10. Full 3D spine models. Bayat et al. © 2022 The Authors