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BioFace3D: A fully automatic pipeline for facial biomarkers extraction of 3D face reconstructions segmented from MRI

arXiv 2410.00711 ↗First posted 1 Oct 2024cs.CV q-bio.QMcited by 0

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Abstract (arXiv)

Facial dysmorphologies have emerged as potential critical indicators in the diagnosis and prognosis of genetic, psychotic and rare disorders. While in certain conditions these dysmorphologies are severe, in other cases may be subtle and not perceivable to the human eye, requiring precise quantitative tools for their identification. Manual coding of facial dysmorphologies is a burdensome task and is subject to inter- and intra-observer variability. To overcome this gap, we present BioFace3D as a fully automatic tool for the calculation of facial biomarkers using facial models reconstructed from magnetic resonance images. The tool is divided into three automatic modules for the extraction of 3D facial models from magnetic resonance images, the registration of homologous 3D landmarks encoding facial morphology, and the calculation of facial biomarkers from anatomical landmarks coordinates using geometric morphometrics techniques.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 52 references that are in the map. First posted on arXiv 1 Oct 2024.

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3 of 52 references.

References · 3

  1. 2021H3D-Net: Few-Shot High-Fidelity 3D Head Reconstructioncited by 81
  2. 2019Multi-view consensus CNN for 3D facial landmark placementcited by 5
  3. 2023Fully automated landmarking and facial segmentation on 3D photographscited by 3

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