BioFace3D: An end-to-end open-source software for automated extraction of potential 3D facial biomarkers from MRI scans
Year: 2025
Type: article
Abstract: Background and Objectives: 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 they may be subtle and not perceivable to the human eye, requiring precise quantitative tools for their identification. Manual annotation remains time-consuming and prone to inter- and intra-observer variability. Existing tools provide partial solutions, but no end-to-end automated pipeline integrates the full process of 3D facial biomarker extraction from medical imaging.Methods and Results: We introduce BioFace3D, an open-source pipeline designed to automate the discovery of potential 3D facial biomarkers from magnetic resonance imaging. BioFace3D consists of three automated modules: (i) 3D facial model extraction from magnetic resonance images, (ii) deep learning-based registration of homologous anatomical landmarks, and (iii) computation of geometric morphometric biomarkers from landmark coordinates.Conclusions: The evaluation of BioFace3D is performed both at a global level and for each module, through a series of experiments with proprietary and public datasets, demonstrating the robustness and usefulness of the tool. Source code, along with pre-trained models, can be found at https://bitbucket.org/cv_her_lasalle/bioface3d.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,350
Funders: U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, Fondation Jérôme Lejeune, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Generalitat de Catalunya, Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya, Eisai, Servier, H. Lundbeck A/S, IXICO, National Institutes of Health, Genentech, Canadian Institutes of Health Research, Agència de Gestió d'Ajuts Universitaris i de Recerca, Instituto de Salud Carlos III, European Regional Development Fund, Agencia Estatal de Investigación, European Social Fund, Ministerio de Universidades
Awards: G1298807586, G138293270, G1554142629, G1593117279, G1650819308, G1880935189, Alzheimer's Disease Neuroimaging Initiative, G2100670906, G2152643862, G2189010064, G2262748287, G228326815, G2340207221, G2423387114, G2471646051, G2522063444, G2835601961, G29951154, G3005324705, G3131374986, G3216574877, G3361607679, G3480869486, G3553156159, G3710456697, G3752451908, G3815383569, G3870774570, G3908963977, G4119534169, G425668148, G43180419, G4475667458, G4501223628, G451917667, G4800177743, G5207404921, G5209990037, G528601746, G5324093878, G5365730499, EFFECTS OF TRAUMATIC BRAIN INJURY (TBI) AND POST TRAUMATIC STRESS DISORDER (PTSD) ON ALZHEIMER'S DISEASE (AD) IN VETERANS USING IMAGING AND BIOMARKERS IN THE AD NEUROIMAGING INITIATIVE (ADNI)", G5654639750, G5740349702, G5850682332, G5852091828, G5967599077, G613619302, G6173816828, G6210868510, G6371410416, G6412110892, G6447063303, G6719828067, G6792506723, G6899163935, G7084143925, G72415811, G7298697282, G764699806, G7799614282, G781725486, G7843172932, G8228018387, G8281378126, G839208290, G8852128998, G8895907669, G8897063270, G8957659042, G9000039018, G9000122335
OpenAlex ID: W4413239726