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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.00711 |
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| _version_ | 1866916418877915136 |
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| author | Heredia-Lidón, Álvaro Echeverry-Quiceno, Luis M. González, Alejandro Hostalet, Noemí Pomarol-Clotet, Edith Fortea, Juan Fatjó-Vilas, Mar Martínez-Abadías, Neus Sevillano, Xavier |
| author_facet | Heredia-Lidón, Álvaro Echeverry-Quiceno, Luis M. González, Alejandro Hostalet, Noemí Pomarol-Clotet, Edith Fortea, Juan Fatjó-Vilas, Mar Martínez-Abadías, Neus Sevillano, Xavier |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_00711 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | BioFace3D: A fully automatic pipeline for facial biomarkers extraction of 3D face reconstructions segmented from MRI Heredia-Lidón, Álvaro Echeverry-Quiceno, Luis M. González, Alejandro Hostalet, Noemí Pomarol-Clotet, Edith Fortea, Juan Fatjó-Vilas, Mar Martínez-Abadías, Neus Sevillano, Xavier Computer Vision and Pattern Recognition Quantitative Methods 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. |
| title | BioFace3D: A fully automatic pipeline for facial biomarkers extraction of 3D face reconstructions segmented from MRI |
| topic | Computer Vision and Pattern Recognition Quantitative Methods |
| url | https://arxiv.org/abs/2410.00711 |