Three-dimensional virtual planning in mandibular advancement surgery: soft tissue prediction based on deep learning. R ter Horst, H van Weert, T Loonen, S Bergé, S Vinayahalingam, F Baan, T Maal, G de Jong, T Xi.

3dMD Customer Research, Computer Science | Computer Vision, Medical, 3dMDface, Oral and Maxillofacial, Orthognathic

This study focused on developing a novel deep-learning (DL)-based algorithm to predict the virtual soft tissue profile after mandibular advancement surgery and comparing its accuracy with the mass tensor model (MTM).

Details

Evaluating effects of focal length and viewing angle in a comparison of recent face landmark and alignment methods. X Li, J Liu, J Baron et al.

3dMD Customer Research, Computer Science | Computer Vision

The workflow… we first performed facial geometry capture with a 3dMD system; imported into landmarker.io to annotate each face manually to achieve ground-truth; rasterized each face at 49 angles and 6 focal lengths; calculated the ground-truth 2D landmark locations; and analyzed performance of each method by calculating NRMSE error between a method’s predicted landmarks and the 2D ground-truth locations.

Details

Lip morphology estimation models based on three-dimensional images in a modern adult population from China. Jm Zhao, Ll Ji, Mq Han et al.

3dMD Customer Research, Dental, Normative Study

Lips are the main part of the lower facial soft tissue and are vital to forensic facial approximation (FFA). Facial soft tissue thickness (FSTT) and linear measurements in three dimensions are used in the quantitative analysis of lip morphology. With most FSTT analysis methods, the surface of soft tissue is unexplicit. Our study aimed to determine FSTT and explore the relationship between the hard and soft tissues of lips in different skeletal occlusions based on cone-beam CT (CBCT) and 3dMD images in a Chinese population.

Details

Automatic Assessment of 3-Dimensional Facial Soft Tissue Symmetry Before and After Orthognathic Surgery Using a Machine Learning Model. LJ Lo, CT Yang, CT Ho, CH Liao, HH Lin.

3dMD Customer Research, Computer Science | Computer Vision, Medical, 3dMDface, Craniofacial/Cleft, Plastics

This study applied the transfer learning model with a convolutional neural network based on 3-dimensional (3D) contour line features to evaluate the facial symmetry before and after OGS. A total of 158 patients were recruited in a retrospective cohort study for the assessment and comparison of facial symmetry before and after OGS from January 2018 to March 2020. Three-dimensional facial photographs were captured by the 3dMD face system in a natural head position, with eyes looking forward, relaxed facial muscles, and habitual dental occlusion before and at least 6 months after surgery.

Details

Changes in the craniofacial structures and esthetic perceptions of soft-tissue profile alterations after distalization and Herbst appliance treatment. EC Irezli, A Baysal.

3dMD Customer Research, Dental, 3dMDface, Orthodontics

Dentoskeletal and soft-tissue treatment changes were examined objectively by cephalometric analysis and stereophotogrammetry, respectively. Pre- and posttreatment profile views were evaluated subjectively by orthodontists and laypeople using the 7-point Likert scale. Intra- and intergroup comparisons for the repeated measurements were performed with 2-way variance analysis. Bonferroni test was used for multiple comparisons (P ≤0.05).

Details