Harvard and Erasmus MC researchers used 3dMDface system and an AI-based 3D autoencoder to identify a facial trait linked to attention problems and associated prenatal exposures in the Generation R Study cohort.
UT Southwestern and Children’s Health Dallas researchers used 3dMD imaging to compare craniofacial symmetry outcomes between strip craniectomy and fronto-orbital advancement in unicoronal craniosynostosis.
By analyzing head scans, the model accurately classified craniofacial differences in pediatric BWS patients compared with the control group.
This case underscores the need to individualize craniosynostosis treatment strategies for syndromic patients with limited physiologic reserve.
The model outperformed existing methods in patients with craniosynostosis and normative subjects. And the predictions generated by our model could be used to improve the accuracy of surgical planning.
It contains 90k 3dMD system-captured RGB images and 13k 3dMDhand scans from 263 subjects (131 male, 132 female) with diverse skin tones and hand shapes.
Imperial College London trains its 2025 ImHead model for localized 3D head editing with 3dMD’s 4D real-world face data.
This study suggests that for early adolescents in Taiwan, appearance alone may not be a major factor affecting social interactions for children who have undergone CLP reconstructive surgery.
These findings advance the understanding of cutaneous mechanics in sports science and offer empirical guidelines for optimizing compression garment design, particularly for running-related compression legging applications.
The control group were children from the Generation R Study. At ages 9 and 13, 3D facial images were captured using a 3dMDface photogrammetric device.