BioFace3D: A fully automatic pipeline for facial biomarkers extraction of 3D face reconstructions segmented from MRI
<|reference_start|>BioFace3D: A fully automatic pipeline for facial biomarkers extraction of 3D face reconstructions segmented from MRI: 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.<|reference_end|>
@article{heredia-lidón2024bioface3d:,
    title={BioFace3D: A fully automatic pipeline for facial biomarkers extraction
  of 3D face reconstructions segmented from MRI},
    author={'Alvaro Heredia-Lid'on, Luis M. Echeverry-Quiceno, Alejandro
  Gonz'alez, Noem'i Hostalet, Edith Pomarol-Clotet, Juan Fortea, Mar
  Fatj'o-Vilas, Neus Mart'inez-Abad'ias, Xavier Sevillano},
    journal={arXiv preprint arXiv:2410.00711},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.00711},
    primaryClass={cs.CV q-bio.QM}
}