408 patients born between 1991 and 2019, with diagnosed non-syndromic sagittal synostosis, whom underwent FBR, ESC, or SAC in Erasmus MC Sophia Children’s Hospital, and had at least one post-operative 3dMDhead photogrammetry image taken before the age of six, were considered for this study.
Date: October 2024. Source: 3DBodyTech Conference, Lugano, Switzerland. Presenters: Rami R HALLAC, UT Southwestern Medical Center and Children’s Health, Dallas TX, USA, and Chris LANE, 3dMD. Rami R HALLAC Background: Dr. Hallac is an imaging scientist at Children’s Health and an associate professor at UT Southwestern Medical Center. Utilizing 3D imaging, modelling and printing, Dr.…
High-resolution head and face surface data were gathered in a 3dMD system. Head scan data with a range of facial expressions to capture the associated variation in face shape is essential for the design of protective helmets and other head-borne equipment. High-resolution hand size and shape surface data were also recorded to include standardized and functional hand poses, including a flat hand, fist, and various grasps.
SHAPE reads in a patient’s 3D photogram, automatically places a set of craniofacial landmarks, allows for their manual confirmation and correction, and automatically computes both a series of standard clinical craniofacial measurements and machine learning-based metrics of head development prior to building an analysis report for upload to the patient’s electronic medical record.
This study aimed to investigate the impact of head circumference on the accuracy of three-dimensional (3D) facial scans, focusing on trueness and precision.
This study with 1736 subjects evaluates how Martin and Saller’s nasal index correlates to a more comprehensive exploration of nose shape variables using Principal component analysis (PCA) and nonparametric bivariate correlation analysis in the context of the design of head-mounted displays (HMDs).
Three-dimensional (3D) photography allows for the creation of surface models without the need for radiation and has been validated as reliable and equivalent to CT for calvarial measurements.
Tomorrow’s digital ‘human’ creation will be based on AI learning from authentic real-world data of people recorded physically in action with the utmost 3D fidelity.
3dMD facial images and deep transfer learning have been firstly combined for evaluating the facial attractiveness in patients undergoing Orthognathic surgery.
We included all children with scans, either from 3D CT skin reconstructed images or from a 3dMDhead system to undergo the morphometric analyses.